Predicting Covid 19 ICU Hospitalizations¶

April 12 2022 | Hugo Hiraoka | hhiraokawatts@gmail.com

Background¶

The COVID-19 virus has already killed millions of people around the world.

When a COVID-19 patient arrives at the hospital, it is essential to assess if the patient should be sent home or if he/she should be admitted to the hospital because of the high risk of developing severe symptoms that will require admission to the Intensive Care Unit. This could save lives.

How can we determine if COVID-19-positive patients should be admitted to the Intensive Care Unit based on previous patient experiences and outcomes?

We will use data obtained during Triage and Laboratory tests made on COVID-19 patients to predict admission to the hospital should be required.

Problem Definition¶

COVID-19 symptoms can quickly escalate from mild symptoms to severe. Most COVID-19-positive patients first had influenza-like symptoms. But many of those patients ended up in the ICU in a fight to survive.

The objective is to predict if a COVID-19 patient should be admitted to the hospital or treated at home. If a patient is likely to end up in the ICU, he/she should be admitted to the hospital and not allowed to go home.

Objective¶

Classify patients into 2 classes: ICU and no-ICU. Provide insights.

Dataset¶

The dataset can be found at https://www.kaggle.com/datasets/S%C3%ADrio-Libanes/covid19

This dataset was produced by the Hospital Sirio-Libanes in Sao Paulo, Brazil and it contains 231 fields and 1925 entries. It contains Covid-19 patient information gathered during the triage process.

Brazil has been one of the countries with the highest number of COVID-19 deaths and infections.

Target: Predict if the patient should be admitted to the ICU.

covid-icu-dataset-general covid-icu-dataset-vitals covid-icu-dataset-laboratory

The dataset contains the following features:

Demographics 3 features

  • Percentil Age
  • Above 65 Years of age
  • Gender

Commorbities 9 features

Triage Measures, Lab data 42 features

  • Vital Signs : 36 features (6 types)
  • Laboratory : 180 features (36 types)
  • Time window

Target

  • ICU hospitalization or not

Technique¶

This is a supervised classification problem.

Import Libraries¶

In [1]:
#yellowbrick is a machine learning visualization library. We will use it to
#visualize the cluster silhouettes.
!pip install yellowbrick

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In [2]:
# Avoids scroll-in-the-scroll in the entire Notebook
from IPython.display import Javascript
def resize_colab_cell():
  display(Javascript('google.colab.output.setIframeHeight(0, true, {maxHeight: 5000})'))
get_ipython().events.register('pre_run_cell', resize_colab_cell)
In [3]:
%%HTML
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In [11]:
#read tail 10 last rows
covidicu_df.tail(10)
Out[11]:
PATIENT_VISIT_IDENTIFIER AGE_ABOVE65 AGE_PERCENTIL GENDER DISEASE GROUPING 1 DISEASE GROUPING 2 DISEASE GROUPING 3 DISEASE GROUPING 4 DISEASE GROUPING 5 DISEASE GROUPING 6 HTN IMMUNOCOMPROMISED OTHER ALBUMIN_MEDIAN ALBUMIN_MEAN ALBUMIN_MIN ALBUMIN_MAX ALBUMIN_DIFF BE_ARTERIAL_MEDIAN BE_ARTERIAL_MEAN BE_ARTERIAL_MIN BE_ARTERIAL_MAX BE_ARTERIAL_DIFF BE_VENOUS_MEDIAN BE_VENOUS_MEAN BE_VENOUS_MIN BE_VENOUS_MAX BE_VENOUS_DIFF BIC_ARTERIAL_MEDIAN BIC_ARTERIAL_MEAN BIC_ARTERIAL_MIN BIC_ARTERIAL_MAX BIC_ARTERIAL_DIFF BIC_VENOUS_MEDIAN BIC_VENOUS_MEAN BIC_VENOUS_MIN BIC_VENOUS_MAX BIC_VENOUS_DIFF BILLIRUBIN_MEDIAN BILLIRUBIN_MEAN BILLIRUBIN_MIN BILLIRUBIN_MAX BILLIRUBIN_DIFF BLAST_MEDIAN BLAST_MEAN BLAST_MIN BLAST_MAX BLAST_DIFF CALCIUM_MEDIAN CALCIUM_MEAN CALCIUM_MIN CALCIUM_MAX CALCIUM_DIFF CREATININ_MEDIAN CREATININ_MEAN CREATININ_MIN CREATININ_MAX CREATININ_DIFF FFA_MEDIAN FFA_MEAN FFA_MIN FFA_MAX FFA_DIFF GGT_MEDIAN GGT_MEAN GGT_MIN GGT_MAX GGT_DIFF GLUCOSE_MEDIAN GLUCOSE_MEAN GLUCOSE_MIN GLUCOSE_MAX GLUCOSE_DIFF HEMATOCRITE_MEDIAN HEMATOCRITE_MEAN HEMATOCRITE_MIN HEMATOCRITE_MAX HEMATOCRITE_DIFF HEMOGLOBIN_MEDIAN HEMOGLOBIN_MEAN HEMOGLOBIN_MIN HEMOGLOBIN_MAX HEMOGLOBIN_DIFF INR_MEDIAN INR_MEAN INR_MIN INR_MAX INR_DIFF LACTATE_MEDIAN LACTATE_MEAN LACTATE_MIN LACTATE_MAX LACTATE_DIFF LEUKOCYTES_MEDIAN LEUKOCYTES_MEAN LEUKOCYTES_MIN LEUKOCYTES_MAX LEUKOCYTES_DIFF LINFOCITOS_MEDIAN LINFOCITOS_MEAN LINFOCITOS_MIN LINFOCITOS_MAX LINFOCITOS_DIFF NEUTROPHILES_MEDIAN NEUTROPHILES_MEAN NEUTROPHILES_MIN NEUTROPHILES_MAX NEUTROPHILES_DIFF P02_ARTERIAL_MEDIAN P02_ARTERIAL_MEAN P02_ARTERIAL_MIN P02_ARTERIAL_MAX P02_ARTERIAL_DIFF P02_VENOUS_MEDIAN P02_VENOUS_MEAN P02_VENOUS_MIN P02_VENOUS_MAX P02_VENOUS_DIFF PC02_ARTERIAL_MEDIAN PC02_ARTERIAL_MEAN PC02_ARTERIAL_MIN PC02_ARTERIAL_MAX PC02_ARTERIAL_DIFF PC02_VENOUS_MEDIAN PC02_VENOUS_MEAN PC02_VENOUS_MIN PC02_VENOUS_MAX PC02_VENOUS_DIFF PCR_MEDIAN PCR_MEAN PCR_MIN PCR_MAX PCR_DIFF PH_ARTERIAL_MEDIAN PH_ARTERIAL_MEAN PH_ARTERIAL_MIN PH_ARTERIAL_MAX PH_ARTERIAL_DIFF PH_VENOUS_MEDIAN PH_VENOUS_MEAN PH_VENOUS_MIN PH_VENOUS_MAX PH_VENOUS_DIFF PLATELETS_MEDIAN PLATELETS_MEAN PLATELETS_MIN PLATELETS_MAX PLATELETS_DIFF POTASSIUM_MEDIAN POTASSIUM_MEAN POTASSIUM_MIN POTASSIUM_MAX POTASSIUM_DIFF SAT02_ARTERIAL_MEDIAN SAT02_ARTERIAL_MEAN SAT02_ARTERIAL_MIN SAT02_ARTERIAL_MAX SAT02_ARTERIAL_DIFF SAT02_VENOUS_MEDIAN SAT02_VENOUS_MEAN SAT02_VENOUS_MIN SAT02_VENOUS_MAX SAT02_VENOUS_DIFF SODIUM_MEDIAN SODIUM_MEAN SODIUM_MIN SODIUM_MAX SODIUM_DIFF TGO_MEDIAN TGO_MEAN TGO_MIN TGO_MAX TGO_DIFF TGP_MEDIAN TGP_MEAN TGP_MIN TGP_MAX TGP_DIFF TTPA_MEDIAN TTPA_MEAN TTPA_MIN TTPA_MAX TTPA_DIFF UREA_MEDIAN UREA_MEAN UREA_MIN UREA_MAX UREA_DIFF DIMER_MEDIAN DIMER_MEAN DIMER_MIN DIMER_MAX DIMER_DIFF BLOODPRESSURE_DIASTOLIC_MEAN BLOODPRESSURE_SISTOLIC_MEAN HEART_RATE_MEAN RESPIRATORY_RATE_MEAN TEMPERATURE_MEAN OXYGEN_SATURATION_MEAN BLOODPRESSURE_DIASTOLIC_MEDIAN BLOODPRESSURE_SISTOLIC_MEDIAN HEART_RATE_MEDIAN RESPIRATORY_RATE_MEDIAN TEMPERATURE_MEDIAN OXYGEN_SATURATION_MEDIAN BLOODPRESSURE_DIASTOLIC_MIN BLOODPRESSURE_SISTOLIC_MIN HEART_RATE_MIN RESPIRATORY_RATE_MIN TEMPERATURE_MIN OXYGEN_SATURATION_MIN BLOODPRESSURE_DIASTOLIC_MAX BLOODPRESSURE_SISTOLIC_MAX HEART_RATE_MAX RESPIRATORY_RATE_MAX TEMPERATURE_MAX OXYGEN_SATURATION_MAX BLOODPRESSURE_DIASTOLIC_DIFF BLOODPRESSURE_SISTOLIC_DIFF HEART_RATE_DIFF RESPIRATORY_RATE_DIFF TEMPERATURE_DIFF OXYGEN_SATURATION_DIFF BLOODPRESSURE_DIASTOLIC_DIFF_REL BLOODPRESSURE_SISTOLIC_DIFF_REL HEART_RATE_DIFF_REL RESPIRATORY_RATE_DIFF_REL TEMPERATURE_DIFF_REL OXYGEN_SATURATION_DIFF_REL WINDOW ICU
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1919 383 0 40th 1 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 1.000 0.211 0.211 0.211 0.211 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -0.317 -0.317 -0.317 -0.317 -1.000 -0.317 -0.317 -0.317 -0.317 -1.000 -0.976 -0.976 -0.976 -0.976 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 0.357 0.357 0.357 0.357 -1.000 -0.948 -0.948 -0.948 -0.948 -1.000 -0.787 -0.787 -0.787 -0.787 -1.000 -0.714 -0.714 -0.714 -0.714 -1.000 -0.892 -0.892 -0.892 -0.892 -1.000 -0.203 -0.203 -0.203 -0.203 -1.000 -0.220 -0.220 -0.220 -0.220 -1.000 -0.960 -0.960 -0.960 -0.960 -1.000 1.000 1.000 1.000 1.000 -1.000 -0.758 -0.758 -0.758 -0.758 -1.000 -0.691 -0.691 -0.691 -0.691 -1.000 -0.842 -0.842 -0.842 -0.842 -1.000 -0.171 -0.171 -0.171 -0.171 -1.000 -0.704 -0.704 -0.704 -0.704 -1.000 -0.779 -0.779 -0.779 -0.779 -1.000 -0.755 -0.755 -0.755 -0.755 -1.000 -0.869 -0.869 -0.869 -0.869 -1.000 0.234 0.234 0.234 0.234 -1.000 0.364 0.364 0.364 0.364 -1.000 -0.183 -0.183 -0.183 -0.183 -1.000 -0.481 -0.481 -0.481 -0.481 -1.000 0.939 0.939 0.939 0.939 -1.000 0.346 0.346 0.346 0.346 -1.000 0.067 0.067 0.067 0.067 -1.000 -0.997 -0.997 -0.997 -0.997 -1.000 -0.981 -0.981 -0.981 -0.981 -1.000 -0.847 -0.847 -0.847 -0.847 -1.000 -0.933 -0.933 -0.933 -0.933 -1.000 -0.978 -0.978 -0.978 -0.978 -1.000 -0.083 -0.479 -0.190 -0.541 0.036 0.706 -0.160 -0.538 -0.189 -0.517 0.000 0.737 -0.175 -0.375 -0.419 -0.714 0.165 0.798 -0.077 -0.470 -0.030 -0.394 0.043 0.895 -0.478 -0.644 -0.359 -0.588 -0.571 -0.838 -0.553 -0.586 -0.557 -0.573 -0.573 -0.839 ABOVE_12 0
1920 384 0 50th 1 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 1.000 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 0.012 -0.292 0.057 -0.525 0.536 0.789 0.012 -0.292 0.057 -0.517 0.536 0.789 0.175 -0.050 0.145 -0.429 0.714 0.919 -0.299 -0.503 -0.164 -0.576 0.246 0.789 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 0-2 0
1921 384 0 50th 1 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 1.000 0.605 0.605 0.605 0.605 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -0.717 -0.717 -0.717 -0.717 -1.000 -0.317 -0.317 -0.317 -0.317 -1.000 -0.171 -0.171 -0.171 -0.171 -1.000 -0.982 -0.982 -0.982 -0.982 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 0.245 0.245 0.245 0.245 -1.000 -0.935 -0.935 -0.935 -0.935 -1.000 -0.783 -0.783 -0.783 -0.783 -1.000 -0.960 -0.960 -0.960 -0.960 -1.000 -0.862 -0.862 -0.862 -0.862 -1.000 -0.065 -0.065 -0.065 -0.065 -1.000 -0.159 -0.159 -0.159 -0.159 -1.000 -0.957 -0.957 -0.957 -0.957 -1.000 -0.898 -0.898 -0.898 -0.898 -1.000 -0.849 -0.849 -0.849 -0.849 -1.000 -0.687 -0.687 -0.687 -0.687 -1.000 -0.913 -0.913 -0.913 -0.913 -1.000 -0.171 -0.171 -0.171 -0.171 -1.000 -0.858 -0.858 -0.858 -0.858 -1.000 -0.779 -0.779 -0.779 -0.779 -1.000 -0.730 -0.730 -0.730 -0.730 -1.000 -0.906 -0.906 -0.906 -0.906 -1.000 0.234 0.234 0.234 0.234 -1.000 0.424 0.424 0.424 0.424 -1.000 -0.479 -0.479 -0.479 -0.479 -1.000 -0.333 -0.333 -0.333 -0.333 -1.000 0.939 0.939 0.939 0.939 -1.000 -0.333 -0.333 -0.333 -0.333 -1.000 -0.086 -0.086 -0.086 -0.086 -1.000 -0.997 -0.997 -0.997 -0.997 -1.000 -0.992 -0.992 -0.992 -0.992 -1.000 -0.869 -0.869 -0.869 -0.869 -1.000 -0.880 -0.880 -0.880 -0.880 -1.000 -0.980 -0.980 -0.980 -0.980 -1.000 0.086 -0.385 -0.113 -0.593 0.143 0.579 0.086 -0.385 -0.113 -0.586 0.143 0.579 0.237 -0.125 -0.009 -0.500 0.473 0.838 -0.248 -0.568 -0.299 -0.636 -0.072 0.579 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 2-4 0
1922 384 0 50th 1 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 1.000 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 0.086 -0.231 -0.170 -0.593 0.143 0.737 0.086 -0.231 -0.170 -0.586 0.143 0.737 0.237 0.000 -0.060 -0.500 0.473 0.899 -0.248 -0.459 -0.343 -0.636 -0.072 0.737 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 4-6 0
1923 384 0 50th 1 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 1.000 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 0.210 -0.385 -0.189 -0.661 0.286 0.474 0.210 -0.385 -0.189 -0.655 0.286 0.474 0.340 -0.125 -0.077 -0.571 0.560 0.798 -0.162 -0.568 -0.358 -0.697 0.043 0.474 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 6-12 0
1924 384 0 50th 1 0.000 0.000 1.000 0.000 0.000 0.000 0.000 0.000 1.000 0.605 0.605 0.605 0.605 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -0.317 -0.317 -0.317 -0.317 -1.000 -0.317 -0.317 -0.317 -0.317 -1.000 -0.983 -0.983 -0.983 -0.983 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 0.306 0.306 0.306 0.306 -1.000 -0.945 -0.945 -0.945 -0.945 -1.000 -0.825 -0.825 -0.825 -0.825 -1.000 -0.963 -0.963 -0.963 -0.963 -1.000 -0.892 -0.892 -0.892 -0.892 -1.000 -0.157 -0.157 -0.157 -0.157 -1.000 -0.293 -0.293 -0.293 -0.293 -1.000 -0.960 -0.960 -0.960 -0.960 -1.000 1.000 1.000 1.000 1.000 -1.000 -0.851 -0.851 -0.851 -0.851 -1.000 -0.635 -0.635 -0.635 -0.635 -1.000 -0.936 -0.936 -0.936 -0.936 -1.000 -0.171 -0.171 -0.171 -0.171 -1.000 -0.704 -0.704 -0.704 -0.704 -1.000 -0.779 -0.779 -0.779 -0.779 -1.000 -0.755 -0.755 -0.755 -0.755 -1.000 -0.801 -0.801 -0.801 -0.801 -1.000 0.234 0.234 0.234 0.234 -1.000 0.364 0.364 0.364 0.364 -1.000 -0.463 -0.463 -0.463 -0.463 -1.000 -0.444 -0.444 -0.444 -0.444 -1.000 0.939 0.939 0.939 0.939 -1.000 0.346 0.346 0.346 0.346 -1.000 0.200 0.200 0.200 0.200 -1.000 -0.998 -0.998 -0.998 -0.998 -1.000 -0.992 -0.992 -0.992 -0.992 -1.000 -0.847 -0.847 -0.847 -0.847 -1.000 -0.807 -0.807 -0.807 -0.807 -1.000 -0.888 -0.888 -0.888 -0.888 -1.000 -0.185 -0.539 -0.108 -0.610 0.051 0.662 -0.160 -0.538 -0.075 -0.586 0.071 0.632 -0.175 -0.375 -0.248 -0.786 0.187 0.778 -0.248 -0.470 -0.149 -0.515 0.101 0.842 -0.652 -0.644 -0.634 -0.647 -0.548 -0.838 -0.702 -0.586 -0.764 -0.613 -0.551 -0.835 ABOVE_12 0
In [12]:
#characteristics of features
covidicu_df.describe()
Out[12]:
PATIENT_VISIT_IDENTIFIER AGE_ABOVE65 GENDER DISEASE GROUPING 1 DISEASE GROUPING 2 DISEASE GROUPING 3 DISEASE GROUPING 4 DISEASE GROUPING 5 DISEASE GROUPING 6 HTN IMMUNOCOMPROMISED OTHER ALBUMIN_MEDIAN ALBUMIN_MEAN ALBUMIN_MIN ALBUMIN_MAX ALBUMIN_DIFF BE_ARTERIAL_MEDIAN BE_ARTERIAL_MEAN BE_ARTERIAL_MIN BE_ARTERIAL_MAX BE_ARTERIAL_DIFF BE_VENOUS_MEDIAN BE_VENOUS_MEAN BE_VENOUS_MIN BE_VENOUS_MAX BE_VENOUS_DIFF BIC_ARTERIAL_MEDIAN BIC_ARTERIAL_MEAN BIC_ARTERIAL_MIN BIC_ARTERIAL_MAX BIC_ARTERIAL_DIFF BIC_VENOUS_MEDIAN BIC_VENOUS_MEAN BIC_VENOUS_MIN BIC_VENOUS_MAX BIC_VENOUS_DIFF BILLIRUBIN_MEDIAN BILLIRUBIN_MEAN BILLIRUBIN_MIN BILLIRUBIN_MAX BILLIRUBIN_DIFF BLAST_MEDIAN BLAST_MEAN BLAST_MIN BLAST_MAX BLAST_DIFF CALCIUM_MEDIAN CALCIUM_MEAN CALCIUM_MIN CALCIUM_MAX CALCIUM_DIFF CREATININ_MEDIAN CREATININ_MEAN CREATININ_MIN CREATININ_MAX CREATININ_DIFF FFA_MEDIAN FFA_MEAN FFA_MIN FFA_MAX FFA_DIFF GGT_MEDIAN GGT_MEAN GGT_MIN GGT_MAX GGT_DIFF GLUCOSE_MEDIAN GLUCOSE_MEAN GLUCOSE_MIN GLUCOSE_MAX GLUCOSE_DIFF HEMATOCRITE_MEDIAN HEMATOCRITE_MEAN HEMATOCRITE_MIN HEMATOCRITE_MAX HEMATOCRITE_DIFF HEMOGLOBIN_MEDIAN HEMOGLOBIN_MEAN HEMOGLOBIN_MIN HEMOGLOBIN_MAX HEMOGLOBIN_DIFF INR_MEDIAN INR_MEAN INR_MIN INR_MAX INR_DIFF LACTATE_MEDIAN LACTATE_MEAN LACTATE_MIN LACTATE_MAX LACTATE_DIFF LEUKOCYTES_MEDIAN LEUKOCYTES_MEAN LEUKOCYTES_MIN LEUKOCYTES_MAX LEUKOCYTES_DIFF LINFOCITOS_MEDIAN LINFOCITOS_MEAN LINFOCITOS_MIN LINFOCITOS_MAX LINFOCITOS_DIFF NEUTROPHILES_MEDIAN NEUTROPHILES_MEAN NEUTROPHILES_MIN NEUTROPHILES_MAX NEUTROPHILES_DIFF P02_ARTERIAL_MEDIAN P02_ARTERIAL_MEAN P02_ARTERIAL_MIN P02_ARTERIAL_MAX P02_ARTERIAL_DIFF P02_VENOUS_MEDIAN P02_VENOUS_MEAN P02_VENOUS_MIN P02_VENOUS_MAX P02_VENOUS_DIFF PC02_ARTERIAL_MEDIAN PC02_ARTERIAL_MEAN PC02_ARTERIAL_MIN PC02_ARTERIAL_MAX PC02_ARTERIAL_DIFF PC02_VENOUS_MEDIAN PC02_VENOUS_MEAN PC02_VENOUS_MIN PC02_VENOUS_MAX PC02_VENOUS_DIFF PCR_MEDIAN PCR_MEAN PCR_MIN PCR_MAX PCR_DIFF PH_ARTERIAL_MEDIAN PH_ARTERIAL_MEAN PH_ARTERIAL_MIN PH_ARTERIAL_MAX PH_ARTERIAL_DIFF PH_VENOUS_MEDIAN PH_VENOUS_MEAN PH_VENOUS_MIN PH_VENOUS_MAX PH_VENOUS_DIFF PLATELETS_MEDIAN PLATELETS_MEAN PLATELETS_MIN PLATELETS_MAX PLATELETS_DIFF POTASSIUM_MEDIAN POTASSIUM_MEAN POTASSIUM_MIN POTASSIUM_MAX POTASSIUM_DIFF SAT02_ARTERIAL_MEDIAN SAT02_ARTERIAL_MEAN SAT02_ARTERIAL_MIN SAT02_ARTERIAL_MAX SAT02_ARTERIAL_DIFF SAT02_VENOUS_MEDIAN SAT02_VENOUS_MEAN SAT02_VENOUS_MIN SAT02_VENOUS_MAX SAT02_VENOUS_DIFF SODIUM_MEDIAN SODIUM_MEAN SODIUM_MIN SODIUM_MAX SODIUM_DIFF TGO_MEDIAN TGO_MEAN TGO_MIN TGO_MAX TGO_DIFF TGP_MEDIAN TGP_MEAN TGP_MIN TGP_MAX TGP_DIFF TTPA_MEDIAN TTPA_MEAN TTPA_MIN TTPA_MAX TTPA_DIFF UREA_MEDIAN UREA_MEAN UREA_MIN UREA_MAX UREA_DIFF DIMER_MEDIAN DIMER_MEAN DIMER_MIN DIMER_MAX DIMER_DIFF BLOODPRESSURE_DIASTOLIC_MEAN BLOODPRESSURE_SISTOLIC_MEAN HEART_RATE_MEAN RESPIRATORY_RATE_MEAN TEMPERATURE_MEAN OXYGEN_SATURATION_MEAN BLOODPRESSURE_DIASTOLIC_MEDIAN BLOODPRESSURE_SISTOLIC_MEDIAN HEART_RATE_MEDIAN RESPIRATORY_RATE_MEDIAN TEMPERATURE_MEDIAN OXYGEN_SATURATION_MEDIAN BLOODPRESSURE_DIASTOLIC_MIN BLOODPRESSURE_SISTOLIC_MIN HEART_RATE_MIN RESPIRATORY_RATE_MIN TEMPERATURE_MIN OXYGEN_SATURATION_MIN BLOODPRESSURE_DIASTOLIC_MAX BLOODPRESSURE_SISTOLIC_MAX HEART_RATE_MAX RESPIRATORY_RATE_MAX TEMPERATURE_MAX OXYGEN_SATURATION_MAX BLOODPRESSURE_DIASTOLIC_DIFF BLOODPRESSURE_SISTOLIC_DIFF HEART_RATE_DIFF RESPIRATORY_RATE_DIFF TEMPERATURE_DIFF OXYGEN_SATURATION_DIFF BLOODPRESSURE_DIASTOLIC_DIFF_REL BLOODPRESSURE_SISTOLIC_DIFF_REL HEART_RATE_DIFF_REL RESPIRATORY_RATE_DIFF_REL TEMPERATURE_DIFF_REL OXYGEN_SATURATION_DIFF_REL ICU
count 1925.000 1925.000 1925.000 1920.000 1920.000 1920.000 1920.000 1920.000 1920.000 1920.000 1920.000 1920.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 821.000 1240.000 1240.000 1240.000 1177.000 1231.000 1239.000 1240.000 1240.000 1240.000 1177.000 1231.000 1239.000 1240.000 1240.000 1240.000 1177.000 1231.000 1239.000 1240.000 1240.000 1240.000 1177.000 1231.000 1239.000 1240.000 1240.000 1240.000 1177.000 1231.000 1239.000 1240.000 1240.000 1240.000 1177.000 1231.000 1239.000 1925.000
mean 192.000 0.468 0.369 0.108 0.028 0.098 0.020 0.128 0.047 0.213 0.158 0.810 0.529 0.529 0.529 0.529 -1.000 -0.963 -0.963 -0.963 -0.963 -1.000 -0.931 -0.931 -0.931 -0.931 -1.000 -0.311 -0.311 -0.311 -0.311 -1.000 -0.312 -0.312 -0.312 -0.312 -1.000 -0.946 -0.946 -0.946 -0.946 -1.000 -0.994 -0.994 -0.994 -0.994 -1.000 0.330 0.330 0.330 0.330 -1.000 -0.891 -0.891 -0.891 -0.891 -1.000 -0.723 -0.723 -0.723 -0.723 -1.000 -0.920 -0.920 -0.920 -0.920 -1.000 -0.862 -0.862 -0.862 -0.862 -1.000 -0.161 -0.161 -0.161 -0.161 -1.000 -0.202 -0.202 -0.202 -0.202 -1.000 -0.937 -0.937 -0.937 -0.937 -1.000 0.267 0.267 0.267 0.267 -1.000 -0.741 -0.741 -0.741 -0.741 -1.000 -0.710 -0.710 -0.710 -0.710 -1.000 -0.813 -0.813 -0.813 -0.813 -1.000 -0.176 -0.176 -0.176 -0.176 -1.000 -0.675 -0.675 -0.675 -0.675 -1.000 -0.778 -0.778 -0.778 -0.778 -1.000 -0.756 -0.756 -0.756 -0.756 -1.000 -0.846 -0.846 -0.846 -0.846 -1.000 0.237 0.237 0.237 0.237 -1.000 0.369 0.369 0.369 0.369 -1.000 -0.414 -0.414 -0.414 -0.414 -1.000 -0.526 -0.526 -0.526 -0.526 -1.000 0.914 0.914 0.914 0.914 -1.000 0.332 0.332 0.332 0.332 -1.000 -0.053 -0.053 -0.053 -0.053 -1.000 -0.991 -0.991 -0.991 -0.991 -1.000 -0.982 -0.982 -0.982 -0.982 -1.000 -0.822 -0.822 -0.822 -0.822 -1.000 -0.830 -0.830 -0.830 -0.830 -1.000 -0.954 -0.954 -0.954 -0.954 -1.000 -0.094 -0.333 -0.265 -0.439 0.067 0.743 -0.098 -0.338 -0.269 -0.435 0.064 0.749 -0.041 -0.208 -0.265 -0.483 0.327 0.818 -0.235 -0.400 -0.282 -0.317 0.015 0.819 -0.752 -0.728 -0.754 -0.704 -0.770 -0.887 -0.787 -0.716 -0.818 -0.719 -0.771 -0.887 0.268
std 111.168 0.499 0.483 0.311 0.165 0.297 0.139 0.334 0.211 0.410 0.365 0.392 0.224 0.224 0.224 0.224 0.000 0.161 0.161 0.161 0.161 0.000 0.170 0.170 0.170 0.170 0.000 0.100 0.100 0.100 0.100 0.000 0.119 0.119 0.119 0.119 0.000 0.077 0.077 0.077 0.077 0.000 0.098 0.098 0.098 0.098 0.000 0.126 0.126 0.126 0.126 0.000 0.116 0.116 0.116 0.116 0.000 0.171 0.171 0.171 0.171 0.000 0.152 0.152 0.152 0.152 0.000 0.116 0.116 0.116 0.116 0.000 0.239 0.239 0.239 0.239 0.000 0.254 0.254 0.254 0.254 0.000 0.086 0.086 0.086 0.086 0.000 0.924 0.924 0.924 0.924 0.000 0.149 0.149 0.149 0.149 0.000 0.168 0.168 0.168 0.168 0.000 0.146 0.146 0.146 0.146 0.000 0.158 0.158 0.158 0.158 0.000 0.152 0.152 0.152 0.152 0.000 0.073 0.073 0.073 0.073 0.000 0.095 0.095 0.095 0.095 0.000 0.245 0.245 0.245 0.245 0.000 0.130 0.130 0.130 0.130 0.000 0.131 0.131 0.131 0.131 0.000 0.274 0.274 0.274 0.274 0.000 0.189 0.189 0.189 0.189 0.000 0.150 0.150 0.150 0.150 0.000 0.305 0.305 0.305 0.305 0.000 0.206 0.206 0.206 0.206 0.000 0.075 0.075 0.075 0.075 0.000 0.072 0.072 0.072 0.072 0.000 0.115 0.115 0.115 0.115 0.000 0.151 0.151 0.151 0.151 0.000 0.124 0.124 0.124 0.124 0.000 0.252 0.274 0.247 0.217 0.243 0.133 0.258 0.278 0.253 0.226 0.249 0.126 0.281 0.278 0.273 0.278 0.216 0.283 0.271 0.288 0.296 0.403 0.276 0.141 0.364 0.409 0.366 0.482 0.319 0.296 0.325 0.419 0.270 0.447 0.318 0.297 0.443
min 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 0.000
25% 96.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 1.000 0.605 0.605 0.605 0.605 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -0.317 -0.317 -0.317 -0.317 -1.000 -0.317 -0.317 -0.317 -0.317 -1.000 -0.967 -0.967 -0.967 -0.967 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 0.306 0.306 0.306 0.306 -1.000 -0.931 -0.931 -0.931 -0.931 -1.000 -0.742 -0.742 -0.742 -0.742 -1.000 -0.959 -0.959 -0.959 -0.959 -1.000 -0.892 -0.892 -0.892 -0.892 -1.000 -0.291 -0.291 -0.291 -0.291 -1.000 -0.341 -0.341 -0.341 -0.341 -1.000 -0.960 -0.960 -0.960 -0.960 -1.000 -0.895 -0.895 -0.895 -0.895 -1.000 -0.832 -0.832 -0.832 -0.832 -1.000 -0.828 -0.828 -0.828 -0.828 -1.000 -0.897 -0.897 -0.897 -0.897 -1.000 -0.171 -0.171 -0.171 -0.171 -1.000 -0.704 -0.704 -0.704 -0.704 -1.000 -0.779 -0.779 -0.779 -0.779 -1.000 -0.755 -0.755 -0.755 -0.755 -1.000 -0.982 -0.982 -0.982 -0.982 -1.000 0.234 0.234 0.234 0.234 -1.000 0.364 0.364 0.364 0.364 -1.000 -0.605 -0.605 -0.605 -0.605 -1.000 -0.630 -0.630 -0.630 -0.630 -1.000 0.939 0.939 0.939 0.939 -1.000 0.346 0.346 0.346 0.346 -1.000 -0.143 -0.143 -0.143 -0.143 -1.000 -0.997 -0.997 -0.997 -0.997 -1.000 -0.994 -0.994 -0.994 -0.994 -1.000 -0.847 -0.847 -0.847 -0.847 -1.000 -0.899 -0.899 -0.899 -0.899 -1.000 -0.979 -0.979 -0.979 -0.979 -1.000 -0.263 -0.523 -0.421 -0.553 -0.103 0.684 -0.284 -0.538 -0.434 -0.517 -0.107 0.684 -0.196 -0.375 -0.453 -0.643 0.187 0.818 -0.419 -0.578 -0.478 -0.576 -0.188 0.737 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 0.000
50% 192.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 1.000 0.605 0.605 0.605 0.605 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -0.317 -0.317 -0.317 -0.317 -1.000 -0.317 -0.317 -0.317 -0.317 -1.000 -0.939 -0.939 -0.939 -0.939 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 0.357 0.357 0.357 0.357 -1.000 -0.909 -0.909 -0.909 -0.909 -1.000 -0.742 -0.742 -0.742 -0.742 -1.000 -0.959 -0.959 -0.959 -0.959 -1.000 -0.892 -0.892 -0.892 -0.892 -1.000 -0.132 -0.132 -0.132 -0.132 -1.000 -0.183 -0.183 -0.183 -0.183 -1.000 -0.960 -0.960 -0.960 -0.960 -1.000 1.000 1.000 1.000 1.000 -1.000 -0.774 -0.774 -0.774 -0.774 -1.000 -0.737 -0.737 -0.737 -0.737 -1.000 -0.847 -0.847 -0.847 -0.847 -1.000 -0.171 -0.171 -0.171 -0.171 -1.000 -0.704 -0.704 -0.704 -0.704 -1.000 -0.779 -0.779 -0.779 -0.779 -1.000 -0.755 -0.755 -0.755 -0.755 -1.000 -0.943 -0.943 -0.943 -0.943 -1.000 0.234 0.234 0.234 0.234 -1.000 0.364 0.364 0.364 0.364 -1.000 -0.463 -0.463 -0.463 -0.463 -1.000 -0.519 -0.519 -0.519 -0.519 -1.000 0.939 0.939 0.939 0.939 -1.000 0.346 0.346 0.346 0.346 -1.000 -0.029 -0.029 -0.029 -0.029 -1.000 -0.995 -0.995 -0.995 -0.995 -1.000 -0.987 -0.987 -0.987 -0.987 -1.000 -0.847 -0.847 -0.847 -0.847 -1.000 -0.875 -0.875 -0.875 -0.875 -1.000 -0.978 -0.978 -0.978 -0.978 -1.000 -0.100 -0.374 -0.283 -0.503 0.036 0.737 -0.136 -0.385 -0.283 -0.517 0.036 0.737 -0.031 -0.250 -0.282 -0.500 0.319 0.879 -0.248 -0.459 -0.328 -0.455 -0.014 0.842 -1.000 -0.988 -0.985 -1.000 -0.976 -0.980 -1.000 -0.985 -0.990 -1.000 -0.976 -0.980 0.000
75% 288.000 1.000 1.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 1.000 0.605 0.605 0.605 0.605 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -0.958 -0.958 -0.958 -0.958 -1.000 -0.317 -0.317 -0.317 -0.317 -1.000 -0.317 -0.317 -0.317 -0.317 -1.000 -0.939 -0.939 -0.939 -0.939 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 0.357 0.357 0.357 0.357 -1.000 -0.887 -0.887 -0.887 -0.887 -1.000 -0.742 -0.742 -0.742 -0.742 -1.000 -0.957 -0.957 -0.957 -0.957 -1.000 -0.892 -0.892 -0.892 -0.892 -1.000 -0.002 -0.002 -0.002 -0.002 -1.000 -0.024 -0.024 -0.024 -0.024 -1.000 -0.932 -0.932 -0.932 -0.932 -1.000 1.000 1.000 1.000 1.000 -1.000 -0.703 -0.703 -0.703 -0.703 -1.000 -0.614 -0.614 -0.614 -0.614 -1.000 -0.780 -0.780 -0.780 -0.780 -1.000 -0.171 -0.171 -0.171 -0.171 -1.000 -0.704 -0.704 -0.704 -0.704 -1.000 -0.779 -0.779 -0.779 -0.779 -1.000 -0.755 -0.755 -0.755 -0.755 -1.000 -0.815 -0.815 -0.815 -0.815 -1.000 0.234 0.234 0.234 0.234 -1.000 0.364 0.364 0.364 0.364 -1.000 -0.228 -0.228 -0.228 -0.228 -1.000 -0.444 -0.444 -0.444 -0.444 -1.000 0.939 0.939 0.939 0.939 -1.000 0.346 0.346 0.346 0.346 -1.000 0.067 0.067 0.067 0.067 -1.000 -0.995 -0.995 -0.995 -0.995 -1.000 -0.985 -0.985 -0.985 -0.985 -1.000 -0.837 -0.837 -0.837 -0.837 -1.000 -0.812 -0.812 -0.812 -0.812 -1.000 -0.968 -0.968 -0.968 -0.968 -1.000 0.086 -0.185 -0.132 -0.383 0.206 0.824 0.086 -0.200 -0.132 -0.379 0.196 0.842 0.175 -0.050 -0.094 -0.357 0.473 0.919 -0.077 -0.243 -0.119 -0.212 0.217 0.895 -0.565 -0.558 -0.542 -0.647 -0.595 -0.879 -0.645 -0.522 -0.663 -0.634 -0.595 -0.880 1.000
max 384.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 -1.000 1.000 1.000 1.000 1.000 -1.000 1.000 1.000 1.000 1.000 -1.000 1.000 1.000 1.000 1.000 -1.000 1.000 1.000 1.000 1.000 -1.000 1.000 1.000 1.000 1.000 -1.000 1.000 1.000 1.000 1.000 -1.000 1.000 1.000 1.000 1.000 -1.000 1.000 1.000 1.000 1.000 -1.000 1.000 1.000 1.000 1.000 -1.000 1.000 1.000 1.000 1.000 -1.000 1.000 1.000 1.000 1.000 -1.000 1.000 1.000 1.000 1.000 -1.000 1.000 1.000 1.000 1.000 -1.000 1.000 1.000 1.000 1.000 -1.000 1.000 1.000 1.000 1.000 -1.000 1.000 1.000 1.000 1.000 -1.000 1.000 1.000 1.000 1.000 -1.000 1.000 1.000 1.000 1.000 -1.000 1.000 1.000 1.000 1.000 -1.000 1.000 1.000 1.000 1.000 -1.000 1.000 1.000 1.000 1.000 -1.000 1.000 1.000 1.000 1.000 -1.000 1.000 1.000 1.000 1.000 -1.000 1.000 1.000 1.000 1.000 -1.000 1.000 1.000 1.000 1.000 -1.000 1.000 1.000 1.000 1.000 -1.000 1.000 1.000 1.000 1.000 -1.000 1.000 1.000 1.000 1.000 -1.000 1.000 1.000 1.000 1.000 -1.000 1.000 1.000 1.000 1.000 -1.000 1.000 1.000 1.000 1.000 -1.000 1.000 1.000 1.000 1.000 -1.000 1.000 1.000 1.000 1.000 -1.000 1.000 1.000 1.000 1.000 -1.000 1.000 1.000 1.000 1.000 -1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000

<table style="border-bottom: 1px solid #ddd> Feature Description Data type Values Recommendation PATIENT_VISIT_IDENTIFIER unique patient number INT 0,1,2,3/th> may be useful AGE_ABOVE65 patient older than 65 bool 0 or 1/th> useful AGE_PERCENTIL unique patient number categorical 40th, 60th, 70th, etc may be useful DISEASE_GROUPING_1 MENTAL DISORDER boolean 0 or 1 useful DISEASE_GROUPING_2 DRUG AND ALCOHOL ABUSE boolean 0 or 1 useful DISEASE_GROUPING_3 OBESITY boolean 0 or 1 useful DISEASE_GROUPING_4 COAGULOPATHY boolean 0 or 1 useful DISEASE_GROUPING_5 WEIGHT LOSS boolean 0 or 1 useful DISEASE_GROUPING_6 FLUID AND ELECTROLYTE LOSS boolean 0 or 1 useful

In [13]:
#features data types
covidicu_df.dtypes
Out[13]:
PATIENT_VISIT_IDENTIFIER              int64
AGE_ABOVE65                           int64
AGE_PERCENTIL                        object
GENDER                                int64
DISEASE GROUPING 1                  float64
DISEASE GROUPING 2                  float64
DISEASE GROUPING 3                  float64
DISEASE GROUPING 4                  float64
DISEASE GROUPING 5                  float64
DISEASE GROUPING 6                  float64
HTN                                 float64
IMMUNOCOMPROMISED                   float64
OTHER                               float64
ALBUMIN_MEDIAN                      float64
ALBUMIN_MEAN                        float64
ALBUMIN_MIN                         float64
ALBUMIN_MAX                         float64
ALBUMIN_DIFF                        float64
BE_ARTERIAL_MEDIAN                  float64
BE_ARTERIAL_MEAN                    float64
BE_ARTERIAL_MIN                     float64
BE_ARTERIAL_MAX                     float64
BE_ARTERIAL_DIFF                    float64
BE_VENOUS_MEDIAN                    float64
BE_VENOUS_MEAN                      float64
BE_VENOUS_MIN                       float64
BE_VENOUS_MAX                       float64
BE_VENOUS_DIFF                      float64
BIC_ARTERIAL_MEDIAN                 float64
BIC_ARTERIAL_MEAN                   float64
BIC_ARTERIAL_MIN                    float64
BIC_ARTERIAL_MAX                    float64
BIC_ARTERIAL_DIFF                   float64
BIC_VENOUS_MEDIAN                   float64
BIC_VENOUS_MEAN                     float64
BIC_VENOUS_MIN                      float64
BIC_VENOUS_MAX                      float64
BIC_VENOUS_DIFF                     float64
BILLIRUBIN_MEDIAN                   float64
BILLIRUBIN_MEAN                     float64
BILLIRUBIN_MIN                      float64
BILLIRUBIN_MAX                      float64
BILLIRUBIN_DIFF                     float64
BLAST_MEDIAN                        float64
BLAST_MEAN                          float64
BLAST_MIN                           float64
BLAST_MAX                           float64
BLAST_DIFF                          float64
CALCIUM_MEDIAN                      float64
CALCIUM_MEAN                        float64
CALCIUM_MIN                         float64
CALCIUM_MAX                         float64
CALCIUM_DIFF                        float64
CREATININ_MEDIAN                    float64
CREATININ_MEAN                      float64
CREATININ_MIN                       float64
CREATININ_MAX                       float64
CREATININ_DIFF                      float64
FFA_MEDIAN                          float64
FFA_MEAN                            float64
FFA_MIN                             float64
FFA_MAX                             float64
FFA_DIFF                            float64
GGT_MEDIAN                          float64
GGT_MEAN                            float64
GGT_MIN                             float64
GGT_MAX                             float64
GGT_DIFF                            float64
GLUCOSE_MEDIAN                      float64
GLUCOSE_MEAN                        float64
GLUCOSE_MIN                         float64
GLUCOSE_MAX                         float64
GLUCOSE_DIFF                        float64
HEMATOCRITE_MEDIAN                  float64
HEMATOCRITE_MEAN                    float64
HEMATOCRITE_MIN                     float64
HEMATOCRITE_MAX                     float64
HEMATOCRITE_DIFF                    float64
HEMOGLOBIN_MEDIAN                   float64
HEMOGLOBIN_MEAN                     float64
HEMOGLOBIN_MIN                      float64
HEMOGLOBIN_MAX                      float64
HEMOGLOBIN_DIFF                     float64
INR_MEDIAN                          float64
INR_MEAN                            float64
INR_MIN                             float64
INR_MAX                             float64
INR_DIFF                            float64
LACTATE_MEDIAN                      float64
LACTATE_MEAN                        float64
LACTATE_MIN                         float64
LACTATE_MAX                         float64
LACTATE_DIFF                        float64
LEUKOCYTES_MEDIAN                   float64
LEUKOCYTES_MEAN                     float64
LEUKOCYTES_MIN                      float64
LEUKOCYTES_MAX                      float64
LEUKOCYTES_DIFF                     float64
LINFOCITOS_MEDIAN                   float64
LINFOCITOS_MEAN                     float64
LINFOCITOS_MIN                      float64
LINFOCITOS_MAX                      float64
LINFOCITOS_DIFF                     float64
NEUTROPHILES_MEDIAN                 float64
NEUTROPHILES_MEAN                   float64
NEUTROPHILES_MIN                    float64
NEUTROPHILES_MAX                    float64
NEUTROPHILES_DIFF                   float64
P02_ARTERIAL_MEDIAN                 float64
P02_ARTERIAL_MEAN                   float64
P02_ARTERIAL_MIN                    float64
P02_ARTERIAL_MAX                    float64
P02_ARTERIAL_DIFF                   float64
P02_VENOUS_MEDIAN                   float64
P02_VENOUS_MEAN                     float64
P02_VENOUS_MIN                      float64
P02_VENOUS_MAX                      float64
P02_VENOUS_DIFF                     float64
PC02_ARTERIAL_MEDIAN                float64
PC02_ARTERIAL_MEAN                  float64
PC02_ARTERIAL_MIN                   float64
PC02_ARTERIAL_MAX                   float64
PC02_ARTERIAL_DIFF                  float64
PC02_VENOUS_MEDIAN                  float64
PC02_VENOUS_MEAN                    float64
PC02_VENOUS_MIN                     float64
PC02_VENOUS_MAX                     float64
PC02_VENOUS_DIFF                    float64
PCR_MEDIAN                          float64
PCR_MEAN                            float64
PCR_MIN                             float64
PCR_MAX                             float64
PCR_DIFF                            float64
PH_ARTERIAL_MEDIAN                  float64
PH_ARTERIAL_MEAN                    float64
PH_ARTERIAL_MIN                     float64
PH_ARTERIAL_MAX                     float64
PH_ARTERIAL_DIFF                    float64
PH_VENOUS_MEDIAN                    float64
PH_VENOUS_MEAN                      float64
PH_VENOUS_MIN                       float64
PH_VENOUS_MAX                       float64
PH_VENOUS_DIFF                      float64
PLATELETS_MEDIAN                    float64
PLATELETS_MEAN                      float64
PLATELETS_MIN                       float64
PLATELETS_MAX                       float64
PLATELETS_DIFF                      float64
POTASSIUM_MEDIAN                    float64
POTASSIUM_MEAN                      float64
POTASSIUM_MIN                       float64
POTASSIUM_MAX                       float64
POTASSIUM_DIFF                      float64
SAT02_ARTERIAL_MEDIAN               float64
SAT02_ARTERIAL_MEAN                 float64
SAT02_ARTERIAL_MIN                  float64
SAT02_ARTERIAL_MAX                  float64
SAT02_ARTERIAL_DIFF                 float64
SAT02_VENOUS_MEDIAN                 float64
SAT02_VENOUS_MEAN                   float64
SAT02_VENOUS_MIN                    float64
SAT02_VENOUS_MAX                    float64
SAT02_VENOUS_DIFF                   float64
SODIUM_MEDIAN                       float64
SODIUM_MEAN                         float64
SODIUM_MIN                          float64
SODIUM_MAX                          float64
SODIUM_DIFF                         float64
TGO_MEDIAN                          float64
TGO_MEAN                            float64
TGO_MIN                             float64
TGO_MAX                             float64
TGO_DIFF                            float64
TGP_MEDIAN                          float64
TGP_MEAN                            float64
TGP_MIN                             float64
TGP_MAX                             float64
TGP_DIFF                            float64
TTPA_MEDIAN                         float64
TTPA_MEAN                           float64
TTPA_MIN                            float64
TTPA_MAX                            float64
TTPA_DIFF                           float64
UREA_MEDIAN                         float64
UREA_MEAN                           float64
UREA_MIN                            float64
UREA_MAX                            float64
UREA_DIFF                           float64
DIMER_MEDIAN                        float64
DIMER_MEAN                          float64
DIMER_MIN                           float64
DIMER_MAX                           float64
DIMER_DIFF                          float64
BLOODPRESSURE_DIASTOLIC_MEAN        float64
BLOODPRESSURE_SISTOLIC_MEAN         float64
HEART_RATE_MEAN                     float64
RESPIRATORY_RATE_MEAN               float64
TEMPERATURE_MEAN                    float64
OXYGEN_SATURATION_MEAN              float64
BLOODPRESSURE_DIASTOLIC_MEDIAN      float64
BLOODPRESSURE_SISTOLIC_MEDIAN       float64
HEART_RATE_MEDIAN                   float64
RESPIRATORY_RATE_MEDIAN             float64
TEMPERATURE_MEDIAN                  float64
OXYGEN_SATURATION_MEDIAN            float64
BLOODPRESSURE_DIASTOLIC_MIN         float64
BLOODPRESSURE_SISTOLIC_MIN          float64
HEART_RATE_MIN                      float64
RESPIRATORY_RATE_MIN                float64
TEMPERATURE_MIN                     float64
OXYGEN_SATURATION_MIN               float64
BLOODPRESSURE_DIASTOLIC_MAX         float64
BLOODPRESSURE_SISTOLIC_MAX          float64
HEART_RATE_MAX                      float64
RESPIRATORY_RATE_MAX                float64
TEMPERATURE_MAX                     float64
OXYGEN_SATURATION_MAX               float64
BLOODPRESSURE_DIASTOLIC_DIFF        float64
BLOODPRESSURE_SISTOLIC_DIFF         float64
HEART_RATE_DIFF                     float64
RESPIRATORY_RATE_DIFF               float64
TEMPERATURE_DIFF                    float64
OXYGEN_SATURATION_DIFF              float64
BLOODPRESSURE_DIASTOLIC_DIFF_REL    float64
BLOODPRESSURE_SISTOLIC_DIFF_REL     float64
HEART_RATE_DIFF_REL                 float64
RESPIRATORY_RATE_DIFF_REL           float64
TEMPERATURE_DIFF_REL                float64
OXYGEN_SATURATION_DIFF_REL          float64
WINDOW                               object
ICU                                   int64
dtype: object

Note that only PATIENT_VISIT_IDENTIFIER, AGE_ABOVE65, GENDER, and ICU are INT64 type. AGE_PERCENTIL AND WINDOW are type OBJECT. All other features are FLOAT64.

SANITY CHECK¶

In [15]:
#obtain the
mode1 = covid_icu_df['DISEASE GROUPING 1'].mode()
print(mode1)

0   0.000
Name: DISEASE GROUPING 1, dtype: float64
In [16]:
#for columns DISEASE GROUPING complete NaN cells to the mode
covid_icu_df['DISEASE GROUPING 1']= covid_icu_df['DISEASE GROUPING 1'].fillna(covid_icu_df['DISEASE GROUPING 1'].mode()[0])
covid_icu_df['DISEASE GROUPING 2']= covid_icu_df['DISEASE GROUPING 2'].fillna(covid_icu_df['DISEASE GROUPING 2'].mode()[0])
covid_icu_df['DISEASE GROUPING 3']= covid_icu_df['DISEASE GROUPING 3'].fillna(covid_icu_df['DISEASE GROUPING 3'].mode()[0])
covid_icu_df['DISEASE GROUPING 4']= covid_icu_df['DISEASE GROUPING 4'].fillna(covid_icu_df['DISEASE GROUPING 4'].mode()[0])
covid_icu_df['DISEASE GROUPING 5']= covid_icu_df['DISEASE GROUPING 5'].fillna(covid_icu_df['DISEASE GROUPING 5'].mode()[0])
covid_icu_df['DISEASE GROUPING 6']= covid_icu_df['DISEASE GROUPING 6'].fillna(covid_icu_df['DISEASE GROUPING 6'].mode()[0])
In [17]:
covid_icu_df.isnull().sum().to_frame()
Out[17]:
0
PATIENT_VISIT_IDENTIFIER 0
AGE_ABOVE65 0
AGE_PERCENTIL 0
GENDER 0
DISEASE GROUPING 1 0
DISEASE GROUPING 2 0
DISEASE GROUPING 3 0
DISEASE GROUPING 4 0
DISEASE GROUPING 5 0
DISEASE GROUPING 6 0
HTN 5
IMMUNOCOMPROMISED 5
OTHER 5
ALBUMIN_MEDIAN 1104
ALBUMIN_MEAN 1104
ALBUMIN_MIN 1104
ALBUMIN_MAX 1104
ALBUMIN_DIFF 1104
BE_ARTERIAL_MEDIAN 1104
BE_ARTERIAL_MEAN 1104
BE_ARTERIAL_MIN 1104
BE_ARTERIAL_MAX 1104
BE_ARTERIAL_DIFF 1104
BE_VENOUS_MEDIAN 1104
BE_VENOUS_MEAN 1104
BE_VENOUS_MIN 1104
BE_VENOUS_MAX 1104
BE_VENOUS_DIFF 1104
BIC_ARTERIAL_MEDIAN 1104
BIC_ARTERIAL_MEAN 1104
BIC_ARTERIAL_MIN 1104
BIC_ARTERIAL_MAX 1104
BIC_ARTERIAL_DIFF 1104
BIC_VENOUS_MEDIAN 1104
BIC_VENOUS_MEAN 1104
BIC_VENOUS_MIN 1104
BIC_VENOUS_MAX 1104
BIC_VENOUS_DIFF 1104
BILLIRUBIN_MEDIAN 1104
BILLIRUBIN_MEAN 1104
BILLIRUBIN_MIN 1104
BILLIRUBIN_MAX 1104
BILLIRUBIN_DIFF 1104
BLAST_MEDIAN 1104
BLAST_MEAN 1104
BLAST_MIN 1104
BLAST_MAX 1104
BLAST_DIFF 1104
CALCIUM_MEDIAN 1104
CALCIUM_MEAN 1104
CALCIUM_MIN 1104
CALCIUM_MAX 1104
CALCIUM_DIFF 1104
CREATININ_MEDIAN 1104
CREATININ_MEAN 1104
CREATININ_MIN 1104
CREATININ_MAX 1104
CREATININ_DIFF 1104
FFA_MEDIAN 1104
FFA_MEAN 1104
FFA_MIN 1104
FFA_MAX 1104
FFA_DIFF 1104
GGT_MEDIAN 1104
GGT_MEAN 1104
GGT_MIN 1104
GGT_MAX 1104
GGT_DIFF 1104
GLUCOSE_MEDIAN 1104
GLUCOSE_MEAN 1104
GLUCOSE_MIN 1104
GLUCOSE_MAX 1104
GLUCOSE_DIFF 1104
HEMATOCRITE_MEDIAN 1104
HEMATOCRITE_MEAN 1104
HEMATOCRITE_MIN 1104
HEMATOCRITE_MAX 1104
HEMATOCRITE_DIFF 1104
HEMOGLOBIN_MEDIAN 1104
HEMOGLOBIN_MEAN 1104
HEMOGLOBIN_MIN 1104
HEMOGLOBIN_MAX 1104
HEMOGLOBIN_DIFF 1104
INR_MEDIAN 1104
INR_MEAN 1104
INR_MIN 1104
INR_MAX 1104
INR_DIFF 1104
LACTATE_MEDIAN 1104
LACTATE_MEAN 1104
LACTATE_MIN 1104
LACTATE_MAX 1104
LACTATE_DIFF 1104
LEUKOCYTES_MEDIAN 1104
LEUKOCYTES_MEAN 1104
LEUKOCYTES_MIN 1104
LEUKOCYTES_MAX 1104
LEUKOCYTES_DIFF 1104
LINFOCITOS_MEDIAN 1104
LINFOCITOS_MEAN 1104
LINFOCITOS_MIN 1104
LINFOCITOS_MAX 1104
LINFOCITOS_DIFF 1104
NEUTROPHILES_MEDIAN 1104
NEUTROPHILES_MEAN 1104
NEUTROPHILES_MIN 1104
NEUTROPHILES_MAX 1104
NEUTROPHILES_DIFF 1104
P02_ARTERIAL_MEDIAN 1104
P02_ARTERIAL_MEAN 1104
P02_ARTERIAL_MIN 1104
P02_ARTERIAL_MAX 1104
P02_ARTERIAL_DIFF 1104
P02_VENOUS_MEDIAN 1104
P02_VENOUS_MEAN 1104
P02_VENOUS_MIN 1104
P02_VENOUS_MAX 1104
P02_VENOUS_DIFF 1104
PC02_ARTERIAL_MEDIAN 1104
PC02_ARTERIAL_MEAN 1104
PC02_ARTERIAL_MIN 1104
PC02_ARTERIAL_MAX 1104
PC02_ARTERIAL_DIFF 1104
PC02_VENOUS_MEDIAN 1104
PC02_VENOUS_MEAN 1104
PC02_VENOUS_MIN 1104
PC02_VENOUS_MAX 1104
PC02_VENOUS_DIFF 1104
PCR_MEDIAN 1104
PCR_MEAN 1104
PCR_MIN 1104
PCR_MAX 1104
PCR_DIFF 1104
PH_ARTERIAL_MEDIAN 1104
PH_ARTERIAL_MEAN 1104
PH_ARTERIAL_MIN 1104
PH_ARTERIAL_MAX 1104
PH_ARTERIAL_DIFF 1104
PH_VENOUS_MEDIAN 1104
PH_VENOUS_MEAN 1104
PH_VENOUS_MIN 1104
PH_VENOUS_MAX 1104
PH_VENOUS_DIFF 1104
PLATELETS_MEDIAN 1104
PLATELETS_MEAN 1104
PLATELETS_MIN 1104
PLATELETS_MAX 1104
PLATELETS_DIFF 1104
POTASSIUM_MEDIAN 1104
POTASSIUM_MEAN 1104
POTASSIUM_MIN 1104
POTASSIUM_MAX 1104
POTASSIUM_DIFF 1104
SAT02_ARTERIAL_MEDIAN 1104
SAT02_ARTERIAL_MEAN 1104
SAT02_ARTERIAL_MIN 1104
SAT02_ARTERIAL_MAX 1104
SAT02_ARTERIAL_DIFF 1104
SAT02_VENOUS_MEDIAN 1104
SAT02_VENOUS_MEAN 1104
SAT02_VENOUS_MIN 1104
SAT02_VENOUS_MAX 1104
SAT02_VENOUS_DIFF 1104
SODIUM_MEDIAN 1104
SODIUM_MEAN 1104
SODIUM_MIN 1104
SODIUM_MAX 1104
SODIUM_DIFF 1104
TGO_MEDIAN 1104
TGO_MEAN 1104
TGO_MIN 1104
TGO_MAX 1104
TGO_DIFF 1104
TGP_MEDIAN 1104
TGP_MEAN 1104
TGP_MIN 1104
TGP_MAX 1104
TGP_DIFF 1104
TTPA_MEDIAN 1104
TTPA_MEAN 1104
TTPA_MIN 1104
TTPA_MAX 1104
TTPA_DIFF 1104
UREA_MEDIAN 1104
UREA_MEAN 1104
UREA_MIN 1104
UREA_MAX 1104
UREA_DIFF 1104
DIMER_MEDIAN 1104
DIMER_MEAN 1104
DIMER_MIN 1104
DIMER_MAX 1104
DIMER_DIFF 1104
BLOODPRESSURE_DIASTOLIC_MEAN 685
BLOODPRESSURE_SISTOLIC_MEAN 685
HEART_RATE_MEAN 685
RESPIRATORY_RATE_MEAN 748
TEMPERATURE_MEAN 694
OXYGEN_SATURATION_MEAN 686
BLOODPRESSURE_DIASTOLIC_MEDIAN 685
BLOODPRESSURE_SISTOLIC_MEDIAN 685
HEART_RATE_MEDIAN 685
RESPIRATORY_RATE_MEDIAN 748
TEMPERATURE_MEDIAN 694
OXYGEN_SATURATION_MEDIAN 686
BLOODPRESSURE_DIASTOLIC_MIN 685
BLOODPRESSURE_SISTOLIC_MIN 685
HEART_RATE_MIN 685
RESPIRATORY_RATE_MIN 748
TEMPERATURE_MIN 694
OXYGEN_SATURATION_MIN 686
BLOODPRESSURE_DIASTOLIC_MAX 685
BLOODPRESSURE_SISTOLIC_MAX 685
HEART_RATE_MAX 685
RESPIRATORY_RATE_MAX 748
TEMPERATURE_MAX 694
OXYGEN_SATURATION_MAX 686
BLOODPRESSURE_DIASTOLIC_DIFF 685
BLOODPRESSURE_SISTOLIC_DIFF 685
HEART_RATE_DIFF 685
RESPIRATORY_RATE_DIFF 748
TEMPERATURE_DIFF 694
OXYGEN_SATURATION_DIFF 686
BLOODPRESSURE_DIASTOLIC_DIFF_REL 685
BLOODPRESSURE_SISTOLIC_DIFF_REL 685
HEART_RATE_DIFF_REL 685
RESPIRATORY_RATE_DIFF_REL 748
TEMPERATURE_DIFF_REL 694
OXYGEN_SATURATION_DIFF_REL 686
WINDOW 0
ICU 0

Notice there is are many null values in the dataset, particularly in the laboratory readings.

In [18]:
#for DISEASE GROUPING columns change data type from Float to Int
covid_icu_df["DISEASE GROUPING 1"] = covid_icu_df["DISEASE GROUPING 1"].astype("int64")
covid_icu_df["DISEASE GROUPING 2"] = covid_icu_df["DISEASE GROUPING 2"].astype("int64")
covid_icu_df["DISEASE GROUPING 3"] = covid_icu_df["DISEASE GROUPING 3"].astype("int64")
covid_icu_df["DISEASE GROUPING 4"] = covid_icu_df["DISEASE GROUPING 4"].astype("int64")
covid_icu_df["DISEASE GROUPING 5"] = covid_icu_df["DISEASE GROUPING 5"].astype("int64")
covid_icu_df["DISEASE GROUPING 6"] = covid_icu_df["DISEASE GROUPING 6"].astype("int64")
In [20]:
#focus on AGE_PERCENTIL column
covid_icu_df['AGE_PERCENTIL'].unique()
Out[20]:
array(['60th', '90th', '10th', '40th', '70th', '20th', '50th', '80th',
       '30th', 'Above 90th'], dtype=object)
In [21]:
#dummies
covid_icu_df = pd.get_dummies(covid_icu_df,columns=['AGE_PERCENTIL'])
In [22]:
#focus on AGE_PERCENTIL column
covid_icu_df['WINDOW'].unique()
Out[22]:
array(['0-2', '2-4', '4-6', '6-12', 'ABOVE_12'], dtype=object)
In [23]:
#dummies
covid_icu_df = pd.get_dummies(covid_icu_df,columns=['WINDOW'])
In [25]:
covid_icu_df.head()
Out[25]:
PATIENT_VISIT_IDENTIFIER AGE_ABOVE65 GENDER DISEASE GROUPING 1 DISEASE GROUPING 2 DISEASE GROUPING 3 DISEASE GROUPING 4 DISEASE GROUPING 5 DISEASE GROUPING 6 HTN IMMUNOCOMPROMISED OTHER ALBUMIN_MEDIAN ALBUMIN_MEAN ALBUMIN_MIN ALBUMIN_MAX ALBUMIN_DIFF BE_ARTERIAL_MEDIAN BE_ARTERIAL_MEAN BE_ARTERIAL_MIN BE_ARTERIAL_MAX BE_ARTERIAL_DIFF BE_VENOUS_MEDIAN BE_VENOUS_MEAN BE_VENOUS_MIN BE_VENOUS_MAX BE_VENOUS_DIFF BIC_ARTERIAL_MEDIAN BIC_ARTERIAL_MEAN BIC_ARTERIAL_MIN BIC_ARTERIAL_MAX BIC_ARTERIAL_DIFF BIC_VENOUS_MEDIAN BIC_VENOUS_MEAN BIC_VENOUS_MIN BIC_VENOUS_MAX BIC_VENOUS_DIFF BILLIRUBIN_MEDIAN BILLIRUBIN_MEAN BILLIRUBIN_MIN BILLIRUBIN_MAX BILLIRUBIN_DIFF BLAST_MEDIAN BLAST_MEAN BLAST_MIN BLAST_MAX BLAST_DIFF CALCIUM_MEDIAN CALCIUM_MEAN CALCIUM_MIN CALCIUM_MAX CALCIUM_DIFF CREATININ_MEDIAN CREATININ_MEAN CREATININ_MIN CREATININ_MAX CREATININ_DIFF FFA_MEDIAN FFA_MEAN FFA_MIN FFA_MAX FFA_DIFF GGT_MEDIAN GGT_MEAN GGT_MIN GGT_MAX GGT_DIFF GLUCOSE_MEDIAN GLUCOSE_MEAN GLUCOSE_MIN GLUCOSE_MAX GLUCOSE_DIFF HEMATOCRITE_MEDIAN HEMATOCRITE_MEAN HEMATOCRITE_MIN HEMATOCRITE_MAX HEMATOCRITE_DIFF HEMOGLOBIN_MEDIAN HEMOGLOBIN_MEAN HEMOGLOBIN_MIN HEMOGLOBIN_MAX HEMOGLOBIN_DIFF INR_MEDIAN INR_MEAN INR_MIN INR_MAX INR_DIFF LACTATE_MEDIAN LACTATE_MEAN LACTATE_MIN LACTATE_MAX LACTATE_DIFF LEUKOCYTES_MEDIAN LEUKOCYTES_MEAN LEUKOCYTES_MIN LEUKOCYTES_MAX LEUKOCYTES_DIFF LINFOCITOS_MEDIAN LINFOCITOS_MEAN LINFOCITOS_MIN LINFOCITOS_MAX LINFOCITOS_DIFF NEUTROPHILES_MEDIAN NEUTROPHILES_MEAN NEUTROPHILES_MIN NEUTROPHILES_MAX NEUTROPHILES_DIFF P02_ARTERIAL_MEDIAN P02_ARTERIAL_MEAN P02_ARTERIAL_MIN P02_ARTERIAL_MAX P02_ARTERIAL_DIFF P02_VENOUS_MEDIAN P02_VENOUS_MEAN P02_VENOUS_MIN ... PCR_MIN PCR_MAX PCR_DIFF PH_ARTERIAL_MEDIAN PH_ARTERIAL_MEAN PH_ARTERIAL_MIN PH_ARTERIAL_MAX PH_ARTERIAL_DIFF PH_VENOUS_MEDIAN PH_VENOUS_MEAN PH_VENOUS_MIN PH_VENOUS_MAX PH_VENOUS_DIFF PLATELETS_MEDIAN PLATELETS_MEAN PLATELETS_MIN PLATELETS_MAX PLATELETS_DIFF POTASSIUM_MEDIAN POTASSIUM_MEAN POTASSIUM_MIN POTASSIUM_MAX POTASSIUM_DIFF SAT02_ARTERIAL_MEDIAN SAT02_ARTERIAL_MEAN SAT02_ARTERIAL_MIN SAT02_ARTERIAL_MAX SAT02_ARTERIAL_DIFF SAT02_VENOUS_MEDIAN SAT02_VENOUS_MEAN SAT02_VENOUS_MIN SAT02_VENOUS_MAX SAT02_VENOUS_DIFF SODIUM_MEDIAN SODIUM_MEAN SODIUM_MIN SODIUM_MAX SODIUM_DIFF TGO_MEDIAN TGO_MEAN TGO_MIN TGO_MAX TGO_DIFF TGP_MEDIAN TGP_MEAN TGP_MIN TGP_MAX TGP_DIFF TTPA_MEDIAN TTPA_MEAN TTPA_MIN TTPA_MAX TTPA_DIFF UREA_MEDIAN UREA_MEAN UREA_MIN UREA_MAX UREA_DIFF DIMER_MEDIAN DIMER_MEAN DIMER_MIN DIMER_MAX DIMER_DIFF BLOODPRESSURE_DIASTOLIC_MEAN BLOODPRESSURE_SISTOLIC_MEAN HEART_RATE_MEAN RESPIRATORY_RATE_MEAN TEMPERATURE_MEAN OXYGEN_SATURATION_MEAN BLOODPRESSURE_DIASTOLIC_MEDIAN BLOODPRESSURE_SISTOLIC_MEDIAN HEART_RATE_MEDIAN RESPIRATORY_RATE_MEDIAN TEMPERATURE_MEDIAN OXYGEN_SATURATION_MEDIAN BLOODPRESSURE_DIASTOLIC_MIN BLOODPRESSURE_SISTOLIC_MIN HEART_RATE_MIN RESPIRATORY_RATE_MIN TEMPERATURE_MIN OXYGEN_SATURATION_MIN BLOODPRESSURE_DIASTOLIC_MAX BLOODPRESSURE_SISTOLIC_MAX HEART_RATE_MAX RESPIRATORY_RATE_MAX TEMPERATURE_MAX OXYGEN_SATURATION_MAX BLOODPRESSURE_DIASTOLIC_DIFF BLOODPRESSURE_SISTOLIC_DIFF HEART_RATE_DIFF RESPIRATORY_RATE_DIFF TEMPERATURE_DIFF OXYGEN_SATURATION_DIFF BLOODPRESSURE_DIASTOLIC_DIFF_REL BLOODPRESSURE_SISTOLIC_DIFF_REL HEART_RATE_DIFF_REL RESPIRATORY_RATE_DIFF_REL TEMPERATURE_DIFF_REL OXYGEN_SATURATION_DIFF_REL ICU AGE_PERCENTIL_10th AGE_PERCENTIL_20th AGE_PERCENTIL_30th AGE_PERCENTIL_40th AGE_PERCENTIL_50th AGE_PERCENTIL_60th AGE_PERCENTIL_70th AGE_PERCENTIL_80th AGE_PERCENTIL_90th AGE_PERCENTIL_Above 90th WINDOW_0-2 WINDOW_2-4 WINDOW_4-6 WINDOW_6-12 WINDOW_ABOVE_12
0 0 1 0 0 0 0 0 1 1 0.000 0.000 1.000 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN ... NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 0.086 -0.231 -0.283 -0.593 -0.286 0.737 0.086 -0.231 -0.283 -0.586 -0.286 0.737 0.237 0.000 -0.162 -0.500 0.209 0.899 -0.248 -0.459 -0.433 -0.636 -0.420 0.737 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 0 0 0 0 0 0 1 0 0 0 0 1 0 0 0 0
1 0 1 0 0 0 0 0 1 1 0.000 0.000 1.000 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN ... NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 0.333 -0.231 -0.132 -0.593 0.536 0.579 0.333 -0.231 -0.132 -0.586 0.536 0.579 0.443 0.000 -0.026 -0.500 0.714 0.838 -0.077 -0.459 -0.313 -0.636 0.246 0.579 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0
2 0 1 0 0 0 0 0 1 1 0.000 0.000 1.000 0.605 0.605 0.605 0.605 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -0.317 -0.317 -0.317 -0.317 -1.000 -0.317 -0.317 -0.317 -0.317 -1.000 -0.939 -0.939 -0.939 -0.939 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 0.184 0.184 0.184 0.184 -1.000 -0.868 -0.868 -0.868 -0.868 -1.000 -0.742 -0.742 -0.742 -0.742 -1.000 -0.945 -0.945 -0.945 -0.945 -1.000 -0.892 -0.892 -0.892 -0.892 -1.000 0.090 0.090 0.090 0.090 -1.000 0.110 0.110 0.110 0.110 -1.000 -0.932 -0.932 -0.932 -0.932 -1.000 1.000 1.000 1.000 1.000 -1.000 -0.836 -0.836 -0.836 -0.836 -1.000 -0.915 -0.915 -0.915 -0.915 -1.000 -0.869 -0.869 -0.869 -0.869 -1.000 -0.171 -0.171 -0.171 -0.171 -1.000 -0.704 -0.704 -0.704 ... -0.875 -0.875 -1.000 0.234 0.234 0.234 0.234 -1.000 0.364 0.364 0.364 0.364 -1.000 -0.541 -0.541 -0.541 -0.541 -1.000 -0.519 -0.519 -0.519 -0.519 -1.000 0.939 0.939 0.939 0.939 -1.000 0.346 0.346 0.346 0.346 -1.000 -0.029 -0.029 -0.029 -0.029 -1.000 -0.997 -0.997 -0.997 -0.997 -1.000 -0.991 -0.991 -0.991 -0.991 -1.000 -0.826 -0.826 -0.826 -0.826 -1.000 -0.836 -0.836 -0.836 -0.836 -1.000 -0.995 -0.995 -0.995 -0.995 -1.000 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0
3 0 1 0 0 0 0 0 1 1 0.000 0.000 1.000 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN ... NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN -0.107 0.737 NaN NaN NaN NaN -0.107 0.737 NaN NaN NaN NaN 0.319 0.899 NaN NaN NaN NaN -0.275 0.737 NaN NaN NaN NaN -1.000 -1.000 NaN NaN NaN NaN -1.000 -1.000 0 0 0 0 0 0 1 0 0 0 0 0 0 0 1 0
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5 rows × 244 columns

In [27]:
covid_data = covid_icu_df.copy()
In [28]:
index_lab_start = covid_data.columns.get_loc('ALBUMIN_MEDIAN')
print(index_lab_start)

12
In [29]:
index_lab_end = covid_data.columns.get_loc('DIMER_DIFF')
print(index_lab_end)

191
In [30]:
index_vital_start = covid_data.columns.get_loc('BLOODPRESSURE_DIASTOLIC_MEAN')
print(index_vital_start)

192
In [31]:
index_vital_end = covid_data.columns.get_loc('OXYGEN_SATURATION_DIFF_REL')
print(index_vital_end)

227
In [32]:
#group data
commorbities_list = [i for i in covid_data.columns if "DISEASE" in i]
commorbities_list.append('HTN')
commorbities_list.append('IMMUNOCOMPROMISED')
commorbities_list.append('OTHER')

general_list = [i for i in covid_data.columns if "AGE_" in i]
general_list.append("GENDER")

vitals_list = covid_data.iloc[index_vital_start:,index_vital_end].tolist()
labs_list = covid_data.iloc[index_lab_start:,index_lab_end].tolist()
In [33]:
print(vitals_list)

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In [34]:
print(labs_list)

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In [35]:
print(f"Number of Patients= {len(covid_data.PATIENT_VISIT_IDENTIFIER.unique())}")

Number of Patients= 385
In [36]:
#drop rows missing values
covid_icu_df= covid_data.dropna()
In [38]:
print(f"Number of Patients= {len(covid_icu_df.PATIENT_VISIT_IDENTIFIER.unique())}")

Number of Patients= 377
In [39]:
general_list
Out[39]:
['AGE_ABOVE65',
 'AGE_PERCENTIL_10th',
 'AGE_PERCENTIL_20th',
 'AGE_PERCENTIL_30th',
 'AGE_PERCENTIL_40th',
 'AGE_PERCENTIL_50th',
 'AGE_PERCENTIL_60th',
 'AGE_PERCENTIL_70th',
 'AGE_PERCENTIL_80th',
 'AGE_PERCENTIL_90th',
 'AGE_PERCENTIL_Above 90th',
 'GENDER']
In [40]:
sns.pairplot(covid_icu_df, hue='ICU', vars=['AGE_ABOVE65','GENDER'])
Out[40]:
<seaborn.axisgrid.PairGrid at 0x7b6419e46c80>

Vital Signs

In [41]:
#plot means
sns.pairplot(covid_icu_df, hue='ICU', vars=['BLOODPRESSURE_DIASTOLIC_MEAN','BLOODPRESSURE_SISTOLIC_MEAN','HEART_RATE_MEAN','RESPIRATORY_RATE_MEAN','TEMPERATURE_MEAN','OXYGEN_SATURATION_MEAN'
                                       ])
Out[41]:
<seaborn.axisgrid.PairGrid at 0x7b6419e87220>
In [42]:
#analyze oxygen saturation and temperature
sns.scatterplot(x= 'OXYGEN_SATURATION_MEAN',y='TEMPERATURE_MEAN',hue='ICU',data = covid_icu_df)
Out[42]:
<Axes: xlabel='OXYGEN_SATURATION_MEAN', ylabel='TEMPERATURE_MEAN'>
In [43]:
#plot medians
sns.pairplot(covid_icu_df, hue='ICU', vars=['BLOODPRESSURE_DIASTOLIC_MEDIAN','BLOODPRESSURE_SISTOLIC_MEDIAN','HEART_RATE_MEDIAN','RESPIRATORY_RATE_MEDIAN','TEMPERATURE_MEDIAN','OXYGEN_SATURATION_MEDIAN'
])
Out[43]:
<seaborn.axisgrid.PairGrid at 0x7b64186d7dc0>
In [44]:
#plot Minimums
sns.pairplot(covid_icu_df, hue='ICU', vars=['BLOODPRESSURE_DIASTOLIC_MIN','BLOODPRESSURE_SISTOLIC_MIN','HEART_RATE_MIN','RESPIRATORY_RATE_MIN','TEMPERATURE_MIN','OXYGEN_SATURATION_MIN'])
Out[44]:
<seaborn.axisgrid.PairGrid at 0x7b640ed715a0>
In [45]:
#Plot Maximums
sns.pairplot(covid_icu_df, hue='ICU', vars=['BLOODPRESSURE_DIASTOLIC_MAX','BLOODPRESSURE_SISTOLIC_MAX','HEART_RATE_MAX','RESPIRATORY_RATE_MAX','TEMPERATURE_MAX','OXYGEN_SATURATION_MAX'])
Out[45]:
<seaborn.axisgrid.PairGrid at 0x7b640e43ac80>
In [46]:
#Plot Differentials (Max-Min)
sns.pairplot(covid_icu_df, hue='ICU', vars=['BLOODPRESSURE_DIASTOLIC_DIFF','BLOODPRESSURE_SISTOLIC_DIFF','HEART_RATE_DIFF','RESPIRATORY_RATE_DIFF','TEMPERATURE_DIFF','OXYGEN_SATURATION_DIFF'])
Out[46]:
<seaborn.axisgrid.PairGrid at 0x7b640dbc41f0>
In [47]:
#plot Differential Relatives
sns.pairplot(covid_icu_df, hue='ICU',vars=['BLOODPRESSURE_DIASTOLIC_DIFF_REL','BLOODPRESSURE_SISTOLIC_DIFF_REL','HEART_RATE_DIFF_REL','RESPIRATORY_RATE_DIFF_REL','TEMPERATURE_DIFF_REL','OXYGEN_SATURATION_DIFF_REL'])
Out[47]:
<seaborn.axisgrid.PairGrid at 0x7b640bf2ed10>

Analyzing Laboratory Tests¶

Median

In [49]:
sns.pairplot(covid_data, hue="ICU", vars=['ALBUMIN_MEDIAN','BE_ARTERIAL_MEDIAN','BE_VENOUS_MEDIAN','BIC_ARTERIAL_MEDIAN','BIC_VENOUS_MEDIAN'])
Out[49]:
<seaborn.axisgrid.PairGrid at 0x7b63f695d600>
In [50]:
sns.pairplot(covid_data, hue="ICU", vars=['BILLIRUBIN_MEDIAN','BLAST_MEDIAN','CALCIUM_MEDIAN','CREATININ_MEDIAN','GGT_MEDIAN','GLUCOSE_MEDIAN'])
Out[50]:
<seaborn.axisgrid.PairGrid at 0x7b63db5eb820>
In [51]:
sns.pairplot(covid_data, hue="ICU", vars=['HEMATOCRITE_MEDIAN','HEMOGLOBIN_MEDIAN','INR_MEDIAN','INR_MEDIAN','LACTATE_MEDIAN','LEUKOCYTES_MEDIAN','LINFOCITOS_MEDIAN'])
Out[51]:
<seaborn.axisgrid.PairGrid at 0x7b63db7fbaf0>
In [53]:
sns.pairplot(covid_data, hue="ICU", vars=['NEUTROPHILES_MEDIAN','P02_ARTERIAL_MEDIAN','P02_VENOUS_MEDIAN','PC02_ARTERIAL_MEDIAN'])
Out[53]:
<seaborn.axisgrid.PairGrid at 0x7b63d784df60>
In [55]:
sns.pairplot(covid_data, hue="ICU", vars=['PC02_VENOUS_MEDIAN','PCR_MEDIAN','PH_ARTERIAL_MEDIAN','PH_VENOUS_MEDIAN'])
Out[55]:
<seaborn.axisgrid.PairGrid at 0x7b63d4fa37c0>
In [56]:
sns.pairplot(covid_data, hue="ICU", vars=['PLATELETS_MEDIAN','POTASSIUM_MEDIAN','SAT02_ARTERIAL_MEDIAN','SAT02_VENOUS_MEDIAN','SODIUM_MEDIAN'])
Out[56]:
<seaborn.axisgrid.PairGrid at 0x7b63d48a0e50>

Minimum

In [52]:
sns.pairplot(covid_data, hue="ICU", vars=['ALBUMIN_MIN','BE_ARTERIAL_MIN','BE_VENOUS_MIN','BIC_ARTERIAL_MIN','BIC_VENOUS_MIN'])
Out[52]:
<seaborn.axisgrid.PairGrid at 0x7b63d985b820>
In [57]:
sns.pairplot(covid_data, hue="ICU", vars=['BILLIRUBIN_MIN','BLAST_MIN','CALCIUM_MIN','CREATININ_MIN','GGT_MIN','GLUCOSE_MIN'])
Out[57]:
<seaborn.axisgrid.PairGrid at 0x7b63d3fa2b00>
In [58]:
sns.pairplot(covid_data, hue="ICU", vars=['HEMATOCRITE_MIN','HEMOGLOBIN_MIN','INR_MIN','INR_MIN','LACTATE_MIN','LEUKOCYTES_MIN','LINFOCITOS_MIN'])
Out[58]:
<seaborn.axisgrid.PairGrid at 0x7b63d3379900>
In [59]:
sns.pairplot(covid_data, hue="ICU", vars=['NEUTROPHILES_MIN','P02_ARTERIAL_MIN','P02_VENOUS_MIN','PC02_ARTERIAL_MIN','PC02_VENOUS_MIN','PCR_MIN','PH_ARTERIAL_MIN'])
Out[59]:
<seaborn.axisgrid.PairGrid at 0x7b63d18b22c0>
In [61]:
sns.pairplot(covid_data, hue="ICU", vars=['PH_VENOUS_MIN','PLATELETS_MIN','POTASSIUM_MIN','SAT02_ARTERIAL_MIN'])
Out[61]:
<seaborn.axisgrid.PairGrid at 0x7b63d0818250>
In [62]:
sns.pairplot(covid_data, hue="ICU", vars=['SAT02_VENOUS_MIN','SODIUM_MIN','TGO_MIN','TGP_MIN','TGP_MIN','TTPA_MIN','UREA_MIN','DIMER_MIN'])
Out[62]:
<seaborn.axisgrid.PairGrid at 0x7b63cf813eb0>

Maximum

In [63]:
sns.pairplot(covid_data, hue="ICU", vars=['ALBUMIN_MAX','BE_ARTERIAL_MAX','BE_VENOUS_MAX','BIC_ARTERIAL_MAX','BIC_VENOUS_MAX'])
Out[63]:
<seaborn.axisgrid.PairGrid at 0x7b63ccdf3e20>
In [64]:
sns.pairplot(covid_data, hue="ICU", vars=['BILLIRUBIN_MAX','BLAST_MAX','CALCIUM_MAX','CREATININ_MAX','GGT_MAX','GLUCOSE_MAX'])
Out[64]:
<seaborn.axisgrid.PairGrid at 0x7b63cc190e20>
In [65]:
sns.pairplot(covid_data, hue="ICU", vars=['HEMATOCRITE_MAX','HEMOGLOBIN_MAX','INR_MAX','INR_MAX','LACTATE_MAX','LEUKOCYTES_MAX','LINFOCITOS_MAX','NEUTROPHILES_MAX'])
Out[65]:
<seaborn.axisgrid.PairGrid at 0x7b63ca456320>
In [66]:
sns.pairplot(covid_data, hue="ICU", vars=['P02_ARTERIAL_MAX','P02_VENOUS_MAX','PC02_ARTERIAL_MAX','PC02_VENOUS_MAX','PCR_MAX','PH_ARTERIAL_MAX','PH_VENOUS_MAX'])
Out[66]:
<seaborn.axisgrid.PairGrid at 0x7b63c8fc6230>
In [67]:
sns.pairplot(covid_data, hue="ICU", vars=['PLATELETS_MAX','POTASSIUM_MAX','SAT02_ARTERIAL_MAX','SAT02_VENOUS_MAX','SODIUM_MAX'])
Out[67]:
<seaborn.axisgrid.PairGrid at 0x7b63c6cc6500>
In [68]:
sns.pairplot(covid_data, hue="ICU", vars=['TGO_MAX','TGP_MAX','TGP_MAX','TTPA_MAX','UREA_MAX','DIMER_MAX'])
Out[68]:
<seaborn.axisgrid.PairGrid at 0x7b63c64e7be0>
In [118]:
#create an indepenent variable X
X = covid_icu_df.drop(["ICU"],axis=1)
In [119]:
#create dependant variable y
y = covid_icu_df['ICU']
In [120]:
from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X,y,test_size=0.2,random_state=5)
In [121]:
X_train.head()
Out[121]:
PATIENT_VISIT_IDENTIFIER AGE_ABOVE65 GENDER DISEASE GROUPING 1 DISEASE GROUPING 2 DISEASE GROUPING 3 DISEASE GROUPING 4 DISEASE GROUPING 5 DISEASE GROUPING 6 HTN IMMUNOCOMPROMISED OTHER ALBUMIN_MEDIAN ALBUMIN_MEAN ALBUMIN_MIN ALBUMIN_MAX ALBUMIN_DIFF BE_ARTERIAL_MEDIAN BE_ARTERIAL_MEAN BE_ARTERIAL_MIN BE_ARTERIAL_MAX BE_ARTERIAL_DIFF BE_VENOUS_MEDIAN BE_VENOUS_MEAN BE_VENOUS_MIN BE_VENOUS_MAX BE_VENOUS_DIFF BIC_ARTERIAL_MEDIAN BIC_ARTERIAL_MEAN BIC_ARTERIAL_MIN BIC_ARTERIAL_MAX BIC_ARTERIAL_DIFF BIC_VENOUS_MEDIAN BIC_VENOUS_MEAN BIC_VENOUS_MIN BIC_VENOUS_MAX BIC_VENOUS_DIFF BILLIRUBIN_MEDIAN BILLIRUBIN_MEAN BILLIRUBIN_MIN BILLIRUBIN_MAX BILLIRUBIN_DIFF BLAST_MEDIAN BLAST_MEAN BLAST_MIN BLAST_MAX BLAST_DIFF CALCIUM_MEDIAN CALCIUM_MEAN CALCIUM_MIN CALCIUM_MAX CALCIUM_DIFF CREATININ_MEDIAN CREATININ_MEAN CREATININ_MIN CREATININ_MAX CREATININ_DIFF FFA_MEDIAN FFA_MEAN FFA_MIN FFA_MAX FFA_DIFF GGT_MEDIAN GGT_MEAN GGT_MIN GGT_MAX GGT_DIFF GLUCOSE_MEDIAN GLUCOSE_MEAN GLUCOSE_MIN GLUCOSE_MAX GLUCOSE_DIFF HEMATOCRITE_MEDIAN HEMATOCRITE_MEAN HEMATOCRITE_MIN HEMATOCRITE_MAX HEMATOCRITE_DIFF HEMOGLOBIN_MEDIAN HEMOGLOBIN_MEAN HEMOGLOBIN_MIN HEMOGLOBIN_MAX HEMOGLOBIN_DIFF INR_MEDIAN INR_MEAN INR_MIN INR_MAX INR_DIFF LACTATE_MEDIAN LACTATE_MEAN LACTATE_MIN LACTATE_MAX LACTATE_DIFF LEUKOCYTES_MEDIAN LEUKOCYTES_MEAN LEUKOCYTES_MIN LEUKOCYTES_MAX LEUKOCYTES_DIFF LINFOCITOS_MEDIAN LINFOCITOS_MEAN LINFOCITOS_MIN LINFOCITOS_MAX LINFOCITOS_DIFF NEUTROPHILES_MEDIAN NEUTROPHILES_MEAN NEUTROPHILES_MIN NEUTROPHILES_MAX NEUTROPHILES_DIFF P02_ARTERIAL_MEDIAN P02_ARTERIAL_MEAN P02_ARTERIAL_MIN P02_ARTERIAL_MAX P02_ARTERIAL_DIFF P02_VENOUS_MEDIAN P02_VENOUS_MEAN P02_VENOUS_MIN ... PCR_MEAN PCR_MIN PCR_MAX PCR_DIFF PH_ARTERIAL_MEDIAN PH_ARTERIAL_MEAN PH_ARTERIAL_MIN PH_ARTERIAL_MAX PH_ARTERIAL_DIFF PH_VENOUS_MEDIAN PH_VENOUS_MEAN PH_VENOUS_MIN PH_VENOUS_MAX PH_VENOUS_DIFF PLATELETS_MEDIAN PLATELETS_MEAN PLATELETS_MIN PLATELETS_MAX PLATELETS_DIFF POTASSIUM_MEDIAN POTASSIUM_MEAN POTASSIUM_MIN POTASSIUM_MAX POTASSIUM_DIFF SAT02_ARTERIAL_MEDIAN SAT02_ARTERIAL_MEAN SAT02_ARTERIAL_MIN SAT02_ARTERIAL_MAX SAT02_ARTERIAL_DIFF SAT02_VENOUS_MEDIAN SAT02_VENOUS_MEAN SAT02_VENOUS_MIN SAT02_VENOUS_MAX SAT02_VENOUS_DIFF SODIUM_MEDIAN SODIUM_MEAN SODIUM_MIN SODIUM_MAX SODIUM_DIFF TGO_MEDIAN TGO_MEAN TGO_MIN TGO_MAX TGO_DIFF TGP_MEDIAN TGP_MEAN TGP_MIN TGP_MAX TGP_DIFF TTPA_MEDIAN TTPA_MEAN TTPA_MIN TTPA_MAX TTPA_DIFF UREA_MEDIAN UREA_MEAN UREA_MIN UREA_MAX UREA_DIFF DIMER_MEDIAN DIMER_MEAN DIMER_MIN DIMER_MAX DIMER_DIFF BLOODPRESSURE_DIASTOLIC_MEAN BLOODPRESSURE_SISTOLIC_MEAN HEART_RATE_MEAN RESPIRATORY_RATE_MEAN TEMPERATURE_MEAN OXYGEN_SATURATION_MEAN BLOODPRESSURE_DIASTOLIC_MEDIAN BLOODPRESSURE_SISTOLIC_MEDIAN HEART_RATE_MEDIAN RESPIRATORY_RATE_MEDIAN TEMPERATURE_MEDIAN OXYGEN_SATURATION_MEDIAN BLOODPRESSURE_DIASTOLIC_MIN BLOODPRESSURE_SISTOLIC_MIN HEART_RATE_MIN RESPIRATORY_RATE_MIN TEMPERATURE_MIN OXYGEN_SATURATION_MIN BLOODPRESSURE_DIASTOLIC_MAX BLOODPRESSURE_SISTOLIC_MAX HEART_RATE_MAX RESPIRATORY_RATE_MAX TEMPERATURE_MAX OXYGEN_SATURATION_MAX BLOODPRESSURE_DIASTOLIC_DIFF BLOODPRESSURE_SISTOLIC_DIFF HEART_RATE_DIFF RESPIRATORY_RATE_DIFF TEMPERATURE_DIFF OXYGEN_SATURATION_DIFF BLOODPRESSURE_DIASTOLIC_DIFF_REL BLOODPRESSURE_SISTOLIC_DIFF_REL HEART_RATE_DIFF_REL RESPIRATORY_RATE_DIFF_REL TEMPERATURE_DIFF_REL OXYGEN_SATURATION_DIFF_REL AGE_PERCENTIL_10th AGE_PERCENTIL_20th AGE_PERCENTIL_30th AGE_PERCENTIL_40th AGE_PERCENTIL_50th AGE_PERCENTIL_60th AGE_PERCENTIL_70th AGE_PERCENTIL_80th AGE_PERCENTIL_90th AGE_PERCENTIL_Above 90th WINDOW_0-2 WINDOW_2-4 WINDOW_4-6 WINDOW_6-12 WINDOW_ABOVE_12
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5 rows × 243 columns

In [122]:
from sklearn.svm import SVC
from sklearn.metrics import classification_report, confusion_matrix
In [123]:
svc_model = SVC()
In [124]:
#fit model to training dataset
svc_model.fit(X_train,y_train)
Out[124]:
SVC()
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SVC()
In [125]:
#predict model using test dataset
y_pred = svc_model.predict(X_test)
In [127]:
#confusion matrx
cm = confusion_matrix(y_test,y_pred)
In [128]:
#visialize the matrix
sns.heatmap(cm, annot=True)
Out[128]:
<Axes: >
In [129]:
#analyze oxygen saturation and temperature (data was already normalized)
sns.scatterplot(x= 'OXYGEN_SATURATION_MEAN',y='TEMPERATURE_MEAN',hue='ICU',data = covid_data)
Out[129]:
<Axes: xlabel='OXYGEN_SATURATION_MEAN', ylabel='TEMPERATURE_MEAN'>
In [130]:
print(classification_report(y_test,y_pred))

              precision    recall  f1-score   support

           0       0.60      0.62      0.61        58
           1       0.55      0.53      0.54        51

    accuracy                           0.58       109
   macro avg       0.58      0.58      0.58       109
weighted avg       0.58      0.58      0.58       109

PCA Visualization¶

In [131]:
from sklearn.preprocessing import StandardScaler
scaler = StandardScaler()
In [132]:
scaler.fit(covid_icu_df)
Out[132]:
StandardScaler()
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StandardScaler()
In [133]:
scaled_data = scaler.transform(covid_icu_df)
In [134]:
from sklearn.decomposition import PCA
pca = PCA(n_components = 6)
pca.fit(scaled_data)
Out[134]:
PCA(n_components=6)
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PCA(n_components=6)
In [135]:
x_pca = pca.transform(scaled_data)
In [136]:
scaled_data.shape
Out[136]:
(545, 244)
In [138]:
x_pca.shape
Out[138]:
(545, 6)
In [140]:
plt.figure(figsize=(8,6))
plt.scatter(x_pca[:,0],x_pca[:,1],c=covid_icu_df['ICU'],cmap='rainbow')
plt.xlabel('First principal component')
plt.ylabel('Second Principal Component')
Out[140]:
Text(0, 0.5, 'Second Principal Component')
In [141]:
pca.components_
Out[141]:
array([[-0.00761693,  0.05669759, -0.00423382, ..., -0.02806448,
        -0.03234043,  0.08199382],
       [-0.00292874,  0.00161737, -0.00303475, ...,  0.01933982,
         0.02306678, -0.06624783],
       [ 0.02808364,  0.02700681, -0.02139796, ...,  0.03460649,
         0.04954377, -0.12107301],
       [ 0.01059482, -0.05412719,  0.01151893, ...,  0.00402355,
        -0.00037937,  0.02583137],
       [ 0.00221165, -0.05928388, -0.0176845 , ..., -0.01088458,
        -0.05389467,  0.12949314],
       [-0.01765375, -0.09225914, -0.03498775, ...,  0.02585492,
         0.02150157, -0.06840848]])
In [142]:
from sklearn.linear_model import LogisticRegression
X_train_pca, X_test_pca, y_train, y_test = train_test_split(x_pca, y, test_size=0.2, random_state=30)

model = LogisticRegression(max_iter=1000)
model.fit(X_train_pca, y_train)
model.score(X_test_pca, y_test)
Out[142]:
0.8256880733944955
In [143]:
#lets do for less components
pca = PCA(n_components = 2)
pca.fit(scaled_data)
Out[143]:
PCA(n_components=2)
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PCA(n_components=2)
In [144]:
x_pca = pca.transform(scaled_data)
x_pca.shape
Out[144]:
(545, 2)
In [145]:
plt.figure(figsize=(8,6))
plt.scatter(x_pca[:,0],x_pca[:,1],c=covid_icu_df['ICU'],cmap='rainbow')
plt.xlabel('First principal component')
plt.ylabel('Second Principal Component')
Out[145]:
Text(0, 0.5, 'Second Principal Component')
In [147]:
X_train_pca, X_test_pca, y_train, y_test = train_test_split(x_pca, y, test_size=0.2, random_state=30)

model = LogisticRegression(max_iter=1000)
model.fit(X_train_pca, y_train)
model.score(X_test_pca, y_test)
Out[147]:
0.8165137614678899

Support Vector Machine (SVM)¶

In [148]:
from IPython.display import Image
%matplotlib inline
import numpy as np
import pandas as pd
In [149]:
from matplotlib.colors import ListedColormap
import matplotlib.pyplot as plt

# To check recent matplotlib compatibility
import matplotlib
from distutils.version import LooseVersion
In [150]:
import csv

covid_svc_np = np.array(covid_icu_df)
display(covid_svc_np)

array([[  0.,   1.,   0., ...,   0.,   0.,   1.],
       [  1.,   1.,   1., ...,   0.,   0.,   0.],
       [  1.,   1.,   1., ...,   0.,   1.,   0.],
       ...,
       [383.,   0.,   1., ...,   0.,   0.,   1.],
       [384.,   0.,   1., ...,   0.,   0.,   0.],
       [384.,   0.,   1., ...,   0.,   0.,   1.]])
In [151]:
index_vital_O2 = np.where(covid_svc_np =='OXYGEN_SATURATION_MEAN')
print(index_vital_O2)

(array([], dtype=int64),)
In [152]:
index_vital_TEMP = np.where(covid_svc_np =='TEMPERATURE_MEAN')
print(index_vital_TEMP)

(array([], dtype=int64),)
In [153]:
index_ICU = np.where(covid_svc_np =='ICU')
print(index_ICU)

(array([], dtype=int64),)
In [155]:
#copy first row
covid_label = covid_svc_np[0]
In [157]:
covid_svc_np_nolabel = np.delete(covid_svc_np,(0),axis=0)
In [158]:
display(covid_svc_np_nolabel)

array([[  1.,   1.,   1., ...,   0.,   0.,   0.],
       [  1.,   1.,   1., ...,   0.,   1.,   0.],
       [  1.,   1.,   1., ...,   0.,   0.,   1.],
       ...,
       [383.,   0.,   1., ...,   0.,   0.,   1.],
       [384.,   0.,   1., ...,   0.,   0.,   0.],
       [384.,   0.,   1., ...,   0.,   0.,   1.]])
In [159]:
from sklearn.model_selection import train_test_split

#print(covid_svc_np[:,0])
target = covid_svc_np_nolabel[0:,230]
y= target

X = covid_svc_np_nolabel[:,[197,198]]

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=1, stratify=y)
In [160]:
X[:,[0,1]]
Out[160]:
array([[ 0.89473684, -0.40740741],
       [ 1.        , -0.50617284],
       [ 0.84197658, -0.18518519],
       ...,
       [ 0.70598911, -0.16049383],
       [ 0.57894737,  0.08641975],
       [ 0.6622807 , -0.16049383]])
In [161]:
X.dtype
Out[161]:
dtype('float64')
In [163]:
y.dtype
Out[163]:
dtype('float64')
In [164]:
len(X_train)
Out[164]:
380
In [166]:
len(y_train)
Out[166]:
380
In [167]:
len(X_test)
Out[167]:
164
In [168]:
len(y_test)
Out[168]:
164
In [169]:
from sklearn.svm import SVC
model = SVC()
In [170]:
model.fit(X_train, y_train)
Out[170]:
SVC()
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
SVC()

Multiple Linear Regression¶

In [171]:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib as mpl
from sklearn import linear_model
import seaborn as sns
In [172]:
import statsmodels.api as sm
import statsmodels.formula.api as smf
In [189]:
target = covid_icu_df['ICU']
y=target
In [178]:
#drop_target
X = covid_icu_df.drop(["ICU"],axis=1)
X = covid_icu_df.drop(["PATIENT_VISIT_IDENTIFIER"],axis=1)
X.head()
Out[178]:
AGE_ABOVE65 GENDER DISEASE GROUPING 1 DISEASE GROUPING 2 DISEASE GROUPING 3 DISEASE GROUPING 4 DISEASE GROUPING 5 DISEASE GROUPING 6 HTN IMMUNOCOMPROMISED OTHER ALBUMIN_MEDIAN ALBUMIN_MEAN ALBUMIN_MIN ALBUMIN_MAX ALBUMIN_DIFF BE_ARTERIAL_MEDIAN BE_ARTERIAL_MEAN BE_ARTERIAL_MIN BE_ARTERIAL_MAX BE_ARTERIAL_DIFF BE_VENOUS_MEDIAN BE_VENOUS_MEAN BE_VENOUS_MIN BE_VENOUS_MAX BE_VENOUS_DIFF BIC_ARTERIAL_MEDIAN BIC_ARTERIAL_MEAN BIC_ARTERIAL_MIN BIC_ARTERIAL_MAX BIC_ARTERIAL_DIFF BIC_VENOUS_MEDIAN BIC_VENOUS_MEAN BIC_VENOUS_MIN BIC_VENOUS_MAX BIC_VENOUS_DIFF BILLIRUBIN_MEDIAN BILLIRUBIN_MEAN BILLIRUBIN_MIN BILLIRUBIN_MAX BILLIRUBIN_DIFF BLAST_MEDIAN BLAST_MEAN BLAST_MIN BLAST_MAX BLAST_DIFF CALCIUM_MEDIAN CALCIUM_MEAN CALCIUM_MIN CALCIUM_MAX CALCIUM_DIFF CREATININ_MEDIAN CREATININ_MEAN CREATININ_MIN CREATININ_MAX CREATININ_DIFF FFA_MEDIAN FFA_MEAN FFA_MIN FFA_MAX FFA_DIFF GGT_MEDIAN GGT_MEAN GGT_MIN GGT_MAX GGT_DIFF GLUCOSE_MEDIAN GLUCOSE_MEAN GLUCOSE_MIN GLUCOSE_MAX GLUCOSE_DIFF HEMATOCRITE_MEDIAN HEMATOCRITE_MEAN HEMATOCRITE_MIN HEMATOCRITE_MAX HEMATOCRITE_DIFF HEMOGLOBIN_MEDIAN HEMOGLOBIN_MEAN HEMOGLOBIN_MIN HEMOGLOBIN_MAX HEMOGLOBIN_DIFF INR_MEDIAN INR_MEAN INR_MIN INR_MAX INR_DIFF LACTATE_MEDIAN LACTATE_MEAN LACTATE_MIN LACTATE_MAX LACTATE_DIFF LEUKOCYTES_MEDIAN LEUKOCYTES_MEAN LEUKOCYTES_MIN LEUKOCYTES_MAX LEUKOCYTES_DIFF LINFOCITOS_MEDIAN LINFOCITOS_MEAN LINFOCITOS_MIN LINFOCITOS_MAX LINFOCITOS_DIFF NEUTROPHILES_MEDIAN NEUTROPHILES_MEAN NEUTROPHILES_MIN NEUTROPHILES_MAX NEUTROPHILES_DIFF P02_ARTERIAL_MEDIAN P02_ARTERIAL_MEAN P02_ARTERIAL_MIN P02_ARTERIAL_MAX P02_ARTERIAL_DIFF P02_VENOUS_MEDIAN P02_VENOUS_MEAN P02_VENOUS_MIN P02_VENOUS_MAX ... PCR_MIN PCR_MAX PCR_DIFF PH_ARTERIAL_MEDIAN PH_ARTERIAL_MEAN PH_ARTERIAL_MIN PH_ARTERIAL_MAX PH_ARTERIAL_DIFF PH_VENOUS_MEDIAN PH_VENOUS_MEAN PH_VENOUS_MIN PH_VENOUS_MAX PH_VENOUS_DIFF PLATELETS_MEDIAN PLATELETS_MEAN PLATELETS_MIN PLATELETS_MAX PLATELETS_DIFF POTASSIUM_MEDIAN POTASSIUM_MEAN POTASSIUM_MIN POTASSIUM_MAX POTASSIUM_DIFF SAT02_ARTERIAL_MEDIAN SAT02_ARTERIAL_MEAN SAT02_ARTERIAL_MIN SAT02_ARTERIAL_MAX SAT02_ARTERIAL_DIFF SAT02_VENOUS_MEDIAN SAT02_VENOUS_MEAN SAT02_VENOUS_MIN SAT02_VENOUS_MAX SAT02_VENOUS_DIFF SODIUM_MEDIAN SODIUM_MEAN SODIUM_MIN SODIUM_MAX SODIUM_DIFF TGO_MEDIAN TGO_MEAN TGO_MIN TGO_MAX TGO_DIFF TGP_MEDIAN TGP_MEAN TGP_MIN TGP_MAX TGP_DIFF TTPA_MEDIAN TTPA_MEAN TTPA_MIN TTPA_MAX TTPA_DIFF UREA_MEDIAN UREA_MEAN UREA_MIN UREA_MAX UREA_DIFF DIMER_MEDIAN DIMER_MEAN DIMER_MIN DIMER_MAX DIMER_DIFF BLOODPRESSURE_DIASTOLIC_MEAN BLOODPRESSURE_SISTOLIC_MEAN HEART_RATE_MEAN RESPIRATORY_RATE_MEAN TEMPERATURE_MEAN OXYGEN_SATURATION_MEAN BLOODPRESSURE_DIASTOLIC_MEDIAN BLOODPRESSURE_SISTOLIC_MEDIAN HEART_RATE_MEDIAN RESPIRATORY_RATE_MEDIAN TEMPERATURE_MEDIAN OXYGEN_SATURATION_MEDIAN BLOODPRESSURE_DIASTOLIC_MIN BLOODPRESSURE_SISTOLIC_MIN HEART_RATE_MIN RESPIRATORY_RATE_MIN TEMPERATURE_MIN OXYGEN_SATURATION_MIN BLOODPRESSURE_DIASTOLIC_MAX BLOODPRESSURE_SISTOLIC_MAX HEART_RATE_MAX RESPIRATORY_RATE_MAX TEMPERATURE_MAX OXYGEN_SATURATION_MAX BLOODPRESSURE_DIASTOLIC_DIFF BLOODPRESSURE_SISTOLIC_DIFF HEART_RATE_DIFF RESPIRATORY_RATE_DIFF TEMPERATURE_DIFF OXYGEN_SATURATION_DIFF BLOODPRESSURE_DIASTOLIC_DIFF_REL BLOODPRESSURE_SISTOLIC_DIFF_REL HEART_RATE_DIFF_REL RESPIRATORY_RATE_DIFF_REL TEMPERATURE_DIFF_REL OXYGEN_SATURATION_DIFF_REL ICU AGE_PERCENTIL_10th AGE_PERCENTIL_20th AGE_PERCENTIL_30th AGE_PERCENTIL_40th AGE_PERCENTIL_50th AGE_PERCENTIL_60th AGE_PERCENTIL_70th AGE_PERCENTIL_80th AGE_PERCENTIL_90th AGE_PERCENTIL_Above 90th WINDOW_0-2 WINDOW_2-4 WINDOW_4-6 WINDOW_6-12 WINDOW_ABOVE_12
4 1 0 0 0 0 0 1 1 0.000 0.000 1.000 0.000 0.000 0.000 0.000 -1.000 -0.872 -0.872 -0.872 -0.872 -1.000 -0.864 -0.864 -0.864 -0.864 -1.000 -0.317 -0.317 -0.317 -0.317 -1.000 -0.415 -0.415 -0.415 -0.415 -1.000 -0.979 -0.979 -0.979 -0.979 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 0.327 0.327 0.327 0.327 -1.000 -0.926 -0.926 -0.926 -0.926 -1.000 -0.859 -0.859 -0.859 -0.859 -1.000 -0.669 -0.669 -0.669 -0.669 -1.000 -0.892 -0.892 -0.892 -0.892 -1.000 -0.321 -0.321 -0.321 -0.321 -1.000 -0.354 -0.354 -0.354 -0.354 -1.000 -0.980 -0.980 -0.980 -0.980 -1.000 -0.963 -0.963 -0.963 -0.963 -1.000 -0.763 -0.763 -0.763 -0.763 -1.000 -0.643 -0.643 -0.643 -0.643 -1.000 -0.869 -0.869 -0.869 -0.869 -1.000 -0.366 -0.366 -0.366 -0.366 -1.000 -0.231 -0.231 -0.231 -0.231 ... -1.000 -1.000 -1.000 0.574 0.574 0.574 0.574 -1.000 0.394 0.394 0.394 0.394 -1.000 -0.471 -0.471 -0.471 -0.471 -1.000 -0.667 -0.667 -0.667 -0.667 -1.000 0.848 0.848 0.848 0.848 -1.000 0.926 0.926 0.926 0.926 -1.000 0.143 0.143 0.143 0.143 -1.000 -0.999 -0.999 -0.999 -0.999 -1.000 -0.984 -0.984 -0.984 -0.984 -1.000 -0.847 -0.847 -0.847 -0.847 -1.000 -0.836 -0.836 -0.836 -0.836 -1.000 -0.997 -0.997 -0.997 -0.997 -1.000 -0.243 -0.339 -0.213 -0.318 0.034 0.666 -0.284 -0.377 -0.189 -0.379 0.036 0.632 -0.340 -0.487 -0.573 -0.857 0.099 0.798 -0.077 0.286 0.299 0.273 0.362 0.947 -0.339 0.325 0.115 0.176 -0.238 -0.818 -0.390 0.408 -0.230 0.097 -0.242 -0.814 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1
6 1 1 0 0 0 0 0 0 1.000 1.000 1.000 -0.211 -0.211 -0.211 -0.211 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -0.317 -0.317 -0.317 -0.317 -1.000 -0.220 -0.220 -0.220 -0.220 -1.000 -0.968 -0.968 -0.968 -0.968 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 0.531 0.531 0.531 0.531 -1.000 -0.615 -0.615 -0.615 -0.615 -1.000 -0.770 -0.770 -0.770 -0.770 -1.000 -0.982 -0.982 -0.982 -0.982 -1.000 -0.892 -0.892 -0.892 -0.892 -1.000 -0.870 -0.870 -0.870 -0.870 -1.000 -0.915 -0.915 -0.915 -0.915 -1.000 -0.960 -0.960 -0.960 -0.960 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -0.524 -0.524 -0.524 -0.524 -1.000 -0.859 -0.859 -0.859 -0.859 -1.000 -0.557 -0.557 -0.557 -0.557 -1.000 -0.171 -0.171 -0.171 -0.171 -1.000 1.000 1.000 1.000 1.000 ... -0.834 -0.834 -1.000 0.234 0.234 0.234 0.234 -1.000 -0.061 -0.061 -0.061 -0.061 -1.000 -0.637 -0.637 -0.637 -0.637 -1.000 -0.630 -0.630 -0.630 -0.630 -1.000 0.939 0.939 0.939 0.939 -1.000 1.000 1.000 1.000 1.000 -1.000 -0.257 -0.257 -0.257 -0.257 -1.000 -0.997 -0.997 -0.997 -0.997 -1.000 -0.994 -0.994 -0.994 -0.994 -1.000 -0.847 -0.847 -0.847 -0.847 -1.000 -0.561 -0.561 -0.561 -0.561 -1.000 -0.978 -0.978 -0.978 -0.978 -1.000 -0.407 0.892 -0.226 -0.390 -0.107 0.895 -0.407 0.892 -0.226 -0.379 -0.107 0.895 -0.175 0.912 -0.111 -0.286 0.319 0.960 -0.590 0.330 -0.388 -0.455 -0.275 0.895 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 1 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0
8 1 1 0 0 0 0 0 0 1.000 1.000 1.000 0.605 0.605 0.605 0.605 -1.000 -0.840 -0.840 -0.840 -0.840 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -0.220 -0.220 -0.220 -0.220 -1.000 -0.317 -0.317 -0.317 -0.317 -1.000 -0.939 -0.939 -0.939 -0.939 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 0.367 0.367 0.367 0.367 -1.000 -0.908 -0.908 -0.908 -0.908 -1.000 -0.742 -0.742 -0.742 -0.742 -1.000 -0.959 -0.959 -0.959 -0.959 -1.000 -0.892 -0.892 -0.892 -0.892 -1.000 -0.002 -0.002 -0.002 -0.002 -1.000 0.020 0.020 0.020 0.020 -1.000 -0.987 -0.987 -0.987 -0.987 -1.000 -0.976 -0.976 -0.976 -0.976 -1.000 -0.735 -0.735 -0.735 -0.735 -1.000 -0.614 -0.614 -0.614 -0.614 -1.000 -0.813 -0.813 -0.813 -0.813 -1.000 -0.012 -0.012 -0.012 -0.012 -1.000 -0.704 -0.704 -0.704 -0.704 ... -0.982 -0.982 -1.000 0.149 0.149 0.149 0.149 -1.000 0.364 0.364 0.364 0.364 -1.000 -0.228 -0.228 -0.228 -0.228 -1.000 -0.741 -0.741 -0.741 -0.741 -1.000 0.970 0.970 0.970 0.970 -1.000 0.346 0.346 0.346 0.346 -1.000 0.067 0.067 0.067 0.067 -1.000 -0.995 -0.995 -0.995 -0.995 -1.000 -0.987 -0.987 -0.987 -0.987 -1.000 -0.635 -0.635 -0.635 -0.635 -1.000 -0.880 -0.880 -0.880 -0.880 -1.000 -0.944 -0.944 -0.944 -0.944 -1.000 -0.457 0.532 -0.385 -0.146 0.114 1.000 -0.506 0.631 -0.358 -0.103 0.143 1.000 -0.258 0.475 -0.299 -0.143 0.407 1.000 -0.573 0.168 -0.478 -0.091 -0.014 1.000 -0.913 -0.755 -0.924 -0.765 -0.881 -1.000 -0.907 -0.831 -0.941 -0.817 -0.883 -1.000 1 0 0 0 0 0 0 0 0 1 0 0 0 0 1 0
9 1 1 0 0 0 0 1 0 1.000 1.000 1.000 0.605 0.605 0.605 0.605 -1.000 -0.914 -0.914 -0.914 -0.914 -1.000 -0.916 -0.916 -0.916 -0.916 -1.000 -0.268 -0.268 -0.268 -0.268 -1.000 -0.268 -0.268 -0.268 -0.268 -1.000 -0.939 -0.939 -0.939 -0.939 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 0.531 0.531 0.531 0.531 -1.000 -0.435 -0.435 -0.435 -0.435 -1.000 -0.742 -0.742 -0.742 -0.742 -1.000 -0.959 -0.959 -0.959 -0.959 -1.000 -0.892 -0.892 -0.892 -0.892 -1.000 -0.686 -0.686 -0.686 -0.686 -1.000 -0.720 -0.720 -0.720 -0.720 -1.000 -0.972 -0.972 -0.972 -0.972 -1.000 -0.976 -0.976 -0.976 -0.976 -1.000 -0.703 -0.703 -0.703 -0.703 -1.000 -0.718 -0.718 -0.718 -0.718 -1.000 -0.778 -0.778 -0.778 -0.778 -1.000 0.341 0.341 0.341 0.341 -1.000 -0.574 -0.574 -0.574 -0.574 ... -0.949 -0.949 -1.000 0.362 0.362 0.362 0.362 -1.000 0.364 0.364 0.364 0.364 -1.000 -0.300 -0.300 -0.300 -0.300 -1.000 -0.185 -0.185 -0.185 -0.185 -1.000 1.000 1.000 1.000 1.000 -1.000 0.580 0.580 0.580 0.580 -1.000 -0.314 -0.314 -0.314 -0.314 -1.000 -0.995 -0.995 -0.995 -0.995 -1.000 -0.987 -0.987 -0.987 -0.987 -1.000 -0.826 -0.826 -0.826 -0.826 -1.000 -0.460 -0.460 -0.460 -0.460 -1.000 -0.978 -0.978 -0.978 -0.978 -1.000 -0.178 0.213 -0.141 -0.380 0.011 0.842 -0.185 0.185 -0.170 -0.379 0.000 0.842 -0.588 -0.325 -0.573 -1.000 0.011 0.798 0.556 0.557 0.299 0.758 0.710 1.000 0.513 0.472 0.115 0.765 0.143 -0.798 0.316 0.200 -0.240 0.645 0.140 -0.802 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1
14 0 0 0 0 0 0 0 0 0.000 0.000 1.000 0.605 0.605 0.605 0.605 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 -0.317 -0.317 -0.317 -0.317 -1.000 -0.463 -0.463 -0.463 -0.463 -1.000 -0.939 -0.939 -0.939 -0.939 -1.000 -1.000 -1.000 -1.000 -1.000 -1.000 0.367 0.367 0.367 0.367 -1.000 -0.907 -0.907 -0.907 -0.907 -1.000 -0.742 -0.742 -0.742 -0.742 -1.000 -0.959 -0.959 -0.959 -0.959 -1.000 -0.892 -0.892 -0.892 -0.892 -1.000 0.019 0.019 0.019 0.019 -1.000 0.000 0.000 0.000 0.000 -1.000 -0.960 -0.960 -0.960 -0.960 -1.000 -0.949 -0.949 -0.949 -0.949 -1.000 -0.629 -0.629 -0.629 -0.629 -1.000 -0.730 -0.730 -0.730 -0.730 -1.000 -0.724 -0.724 -0.724 -0.724 -1.000 -0.171 -0.171 -0.171 -0.171 -1.000 -0.479 -0.479 -0.479 -0.479 ... -0.587 -0.587 -1.000 0.234 0.234 0.234 0.234 -1.000 0.424 0.424 0.424 0.424 -1.000 -0.228 -0.228 -0.228 -0.228 -1.000 -0.593 -0.593 -0.593 -0.593 -1.000 0.939 0.939 0.939 0.939 -1.000 0.778 0.778 0.778 0.778 -1.000 -0.143 -0.143 -0.143 -0.143 -1.000 -0.995 -0.995 -0.995 -0.995 -1.000 -0.987 -0.987 -0.987 -0.987 -1.000 -0.847 -0.847 -0.847 -0.847 -1.000 -0.928 -0.928 -0.928 -0.928 -1.000 -0.978 -0.978 -0.978 -0.978 -1.000 -0.181 -0.552 -0.281 -0.544 0.057 0.797 -0.160 -0.538 -0.274 -0.517 0.107 0.789 -0.299 -0.450 -0.487 -0.643 0.143 0.879 -0.248 -0.351 -0.149 -0.455 0.101 0.947 -0.548 -0.436 -0.420 -0.706 -0.500 -0.899 -0.612 -0.343 -0.577 -0.695 -0.505 -0.900 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 1

5 rows × 243 columns

In [179]:
X.shape
Out[179]:
(545, 243)
In [180]:
covid_icu_df.rename(columns = {'WINDOW_0-2':'WINDOW_0_2','WINDOW_2-4':'WINDOW_2_4','WINDOW_4-6':'WINDOW_4_6','WINDOW_6-12':'WINDOW_6_12','WINDOW_ABOVE_12':'WINDOW_ABOVE_12'}, inplace=True)
In [183]:
covid_icu_df.rename(columns = {'AGE_PERCENTIL_Above 90th':'AGE_PERCENTIL_Above_90th'}, inplace=True)
In [184]:
Xc = sm.add_constant(X) #because we use formula.api
linear_regression=sm.OLS(y,Xc)
fitted_model= linear_regression.fit() #model
In [186]:
fitted_model.summary()
Out[186]:
OLS Regression Results
Dep. Variable: ICU R-squared: 1.000
Model: OLS Adj. R-squared: 1.000
Method: Least Squares F-statistic: 3.164e+14
Date: Tue, 29 Aug 2023 Prob (F-statistic): 0.00
Time: 00:36:11 Log-Likelihood: 8286.6
No. Observations: 545 AIC: -1.638e+04
Df Residuals: 447 BIC: -1.596e+04
Df Model: 97
Covariance Type: nonrobust
coef std err t P>|t| [0.025 0.975]
AGE_ABOVE65 2.22e-16 3.83e-08 5.8e-09 1.000 -7.52e-08 7.52e-08
GENDER 6.245e-17 7.51e-09 8.31e-09 1.000 -1.48e-08 1.48e-08
DISEASE GROUPING 1 3.261e-16 1.06e-08 3.08e-08 1.000 -2.08e-08 2.08e-08
DISEASE GROUPING 2 6.939e-17 1.79e-08 3.87e-09 1.000 -3.52e-08 3.52e-08
DISEASE GROUPING 3 -3.123e-17 1.16e-08 -2.68e-09 1.000 -2.29e-08 2.29e-08
DISEASE GROUPING 4 -5.69e-16 2.15e-08 -2.65e-08 1.000 -4.22e-08 4.22e-08
DISEASE GROUPING 5 2.776e-17 1.07e-08 2.59e-09 1.000 -2.11e-08 2.11e-08
DISEASE GROUPING 6 2.845e-16 1.4e-08 2.03e-08 1.000 -2.75e-08 2.75e-08
HTN -2.29e-16 9.22e-09 -2.48e-08 1.000 -1.81e-08 1.81e-08
IMMUNOCOMPROMISED 1.596e-16 9.4e-09 1.7e-08 1.000 -1.85e-08 1.85e-08
OTHER -9.506e-16 1.25e-08 -7.61e-08 1.000 -2.45e-08 2.45e-08
ALBUMIN_MEDIAN -3.109e-15 8.48e-07 -3.67e-09 1.000 -1.67e-06 1.67e-06
ALBUMIN_MEAN -1.421e-14 1.09e-06 -1.3e-08 1.000 -2.14e-06 2.14e-06
ALBUMIN_MIN 1.887e-15 8.58e-07 2.2e-09 1.000 -1.69e-06 1.69e-06
ALBUMIN_MAX 1.132e-14 8.09e-07 1.4e-08 1.000 -1.59e-06 1.59e-06
ALBUMIN_DIFF -1.164e-10 0.287 -4.06e-10 1.000 -0.563 0.563
BE_ARTERIAL_MEDIAN 1.51e-14 1.42e-06 1.06e-08 1.000 -2.8e-06 2.8e-06
BE_ARTERIAL_MEAN 3.553e-15 1.22e-06 2.92e-09 1.000 -2.39e-06 2.39e-06
BE_ARTERIAL_MIN -5.329e-15 8.78e-07 -6.07e-09 1.000 -1.72e-06 1.72e-06
BE_ARTERIAL_MAX -2.132e-14 2.17e-06 -9.82e-09 1.000 -4.26e-06 4.26e-06
BE_ARTERIAL_DIFF 0 0.287 0 1.000 -0.563 0.563
BE_VENOUS_MEDIAN -5.329e-15 1.32e-06 -4.05e-09 1.000 -2.59e-06 2.59e-06
BE_VENOUS_MEAN -1.776e-15 4.45e-07 -4e-09 1.000 -8.74e-07 8.74e-07
BE_VENOUS_MIN 7.105e-15 8.91e-07 7.97e-09 1.000 -1.75e-06 1.75e-06
BE_VENOUS_MAX 2.442e-15 8.11e-07 3.01e-09 1.000 -1.59e-06 1.59e-06
BE_VENOUS_DIFF -6.985e-10 0.287 -2.44e-09 1.000 -0.563 0.563
BIC_ARTERIAL_MEDIAN 0 1.47e-06 0 1.000 -2.89e-06 2.89e-06
BIC_ARTERIAL_MEAN 7.105e-15 5.87e-07 1.21e-08 1.000 -1.15e-06 1.15e-06
BIC_ARTERIAL_MIN -1.776e-15 7.09e-07 -2.5e-09 1.000 -1.39e-06 1.39e-06
BIC_ARTERIAL_MAX 0 2e-06 0 1.000 -3.93e-06 3.93e-06
BIC_ARTERIAL_DIFF -1.164e-10 0.287 -4.06e-10 1.000 -0.563 0.563
BIC_VENOUS_MEDIAN -4.885e-15 1.64e-06 -2.98e-09 1.000 -3.23e-06 3.23e-06
BIC_VENOUS_MEAN 5.329e-15 7.58e-07 7.03e-09 1.000 -1.49e-06 1.49e-06
BIC_VENOUS_MIN -1.132e-14 8.35e-07 -1.36e-08 1.000 -1.64e-06 1.64e-06
BIC_VENOUS_MAX -3.331e-16 8.78e-07 -3.79e-10 1.000 -1.73e-06 1.73e-06
BIC_VENOUS_DIFF -1.397e-09 0.287 -4.87e-09 1.000 -0.563 0.563
BILLIRUBIN_MEDIAN -2.442e-15 4.2e-07 -5.81e-09 1.000 -8.26e-07 8.26e-07
BILLIRUBIN_MEAN 1.998e-15 4.5e-07 4.44e-09 1.000 -8.84e-07 8.84e-07
BILLIRUBIN_MIN 3.553e-15 4.65e-07 7.64e-09 1.000 -9.14e-07 9.14e-07
BILLIRUBIN_MAX -4.441e-15 4.81e-07 -9.23e-09 1.000 -9.46e-07 9.46e-07
BILLIRUBIN_DIFF -8.149e-10 0.287 -2.84e-09 1.000 -0.563 0.563
BLAST_MEDIAN -6.217e-15 6.18e-07 -1.01e-08 1.000 -1.21e-06 1.21e-06
BLAST_MEAN -6.661e-16 3.46e-07 -1.93e-09 1.000 -6.8e-07 6.8e-07
BLAST_MIN -7.105e-15 7.52e-07 -9.44e-09 1.000 -1.48e-06 1.48e-06
BLAST_MAX 1.51e-14 9.23e-07 1.64e-08 1.000 -1.81e-06 1.81e-06
BLAST_DIFF -3.492e-10 0.287 -1.22e-09 1.000 -0.563 0.563
CALCIUM_MEDIAN 5.329e-15 8.45e-07 6.31e-09 1.000 -1.66e-06 1.66e-06
CALCIUM_MEAN -1.776e-15 1.43e-06 -1.24e-09 1.000 -2.81e-06 2.81e-06
CALCIUM_MIN -3.775e-15 5.96e-07 -6.34e-09 1.000 -1.17e-06 1.17e-06
CALCIUM_MAX -3.775e-15 8.43e-07 -4.48e-09 1.000 -1.66e-06 1.66e-06
CALCIUM_DIFF -1.863e-09 0.287 -6.5e-09 1.000 -0.563 0.563
CREATININ_MEDIAN 8.882e-16 8.11e-07 1.09e-09 1.000 -1.59e-06 1.59e-06
CREATININ_MEAN -1.443e-15 3.66e-07 -3.95e-09 1.000 -7.19e-07 7.19e-07
CREATININ_MIN -5.329e-15 7.23e-07 -7.37e-09 1.000 -1.42e-06 1.42e-06
CREATININ_MAX 2.22e-15 5.13e-07 4.33e-09 1.000 -1.01e-06 1.01e-06
CREATININ_DIFF 5.821e-10 0.287 2.03e-09 1.000 -0.563 0.563
FFA_MEDIAN 1.332e-15 5.41e-07 2.46e-09 1.000 -1.06e-06 1.06e-06
FFA_MEAN 8.882e-16 4.1e-07 2.17e-09 1.000 -8.06e-07 8.06e-07
FFA_MIN 0 3.2e-07 0 1.000 -6.3e-07 6.3e-07
FFA_MAX -3.109e-15 3.86e-07 -8.06e-09 1.000 -7.58e-07 7.58e-07
FFA_DIFF -5.821e-10 0.287 -2.03e-09 1.000 -0.563 0.563
GGT_MEDIAN 6.883e-15 6.27e-07 1.1e-08 1.000 -1.23e-06 1.23e-06
GGT_MEAN -2.22e-15 5.96e-07 -3.72e-09 1.000 -1.17e-06 1.17e-06
GGT_MIN -3.553e-15 6.01e-07 -5.91e-09 1.000 -1.18e-06 1.18e-06
GGT_MAX -8.882e-16 1e-06 -8.86e-10 1.000 -1.97e-06 1.97e-06
GGT_DIFF -3.492e-10 0.287 -1.22e-09 1.000 -0.563 0.563
GLUCOSE_MEDIAN -4.441e-15 9.84e-07 -4.51e-09 1.000 -1.93e-06 1.93e-06
GLUCOSE_MEAN 6.661e-15 6.72e-07 9.91e-09 1.000 -1.32e-06 1.32e-06
GLUCOSE_MIN 3.553e-15 5e-07 7.11e-09 1.000 -9.82e-07 9.82e-07
GLUCOSE_MAX -4.441e-15 5.26e-07 -8.45e-09 1.000 -1.03e-06 1.03e-06
GLUCOSE_DIFF -1.164e-09 0.287 -4.06e-09 1.000 -0.563 0.563
HEMATOCRITE_MEDIAN -3.553e-15 4.66e-07 -7.63e-09 1.000 -9.16e-07 9.16e-07
HEMATOCRITE_MEAN 1.11e-15 2.43e-07 4.57e-09 1.000 -4.78e-07 4.78e-07
HEMATOCRITE_MIN -6.439e-15 5.13e-07 -1.26e-08 1.000 -1.01e-06 1.01e-06
HEMATOCRITE_MAX 7.772e-15 7.52e-07 1.03e-08 1.000 -1.48e-06 1.48e-06
HEMATOCRITE_DIFF 3.492e-10 0.287 1.22e-09 1.000 -0.563 0.563
HEMOGLOBIN_MEDIAN 2.72e-15 4.87e-07 5.59e-09 1.000 -9.56e-07 9.56e-07
HEMOGLOBIN_MEAN 4.441e-16 7e-07 6.35e-10 1.000 -1.38e-06 1.38e-06
HEMOGLOBIN_MIN 3.109e-15 5.78e-07 5.38e-09 1.000 -1.14e-06 1.14e-06
HEMOGLOBIN_MAX -6.661e-15 6.06e-07 -1.1e-08 1.000 -1.19e-06 1.19e-06
HEMOGLOBIN_DIFF 6.985e-10 0.287 2.44e-09 1.000 -0.563 0.563
INR_MEDIAN -7.772e-16 2.91e-07 -2.67e-09 1.000 -5.72e-07 5.72e-07
INR_MEAN -4.441e-16 2.54e-07 -1.75e-09 1.000 -4.99e-07 4.99e-07
INR_MIN 7.994e-15 5.45e-07 1.47e-08 1.000 -1.07e-06 1.07e-06
INR_MAX -1.066e-14 7.3e-07 -1.46e-08 1.000 -1.43e-06 1.43e-06
INR_DIFF 9.313e-10 0.287 3.25e-09 1.000 -0.563 0.563
LACTATE_MEDIAN -1.954e-14 1.96e-06 -9.96e-09 1.000 -3.85e-06 3.85e-06
LACTATE_MEAN 4.441e-15 5.95e-07 7.47e-09 1.000 -1.17e-06 1.17e-06
LACTATE_MIN 7.994e-15 8.36e-07 9.56e-09 1.000 -1.64e-06 1.64e-06
LACTATE_MAX 2.331e-15 6.04e-07 3.86e-09 1.000 -1.19e-06 1.19e-06
LACTATE_DIFF 1.164e-09 0.287 4.06e-09 1.000 -0.563 0.563
LEUKOCYTES_MEDIAN -3.886e-16 3.74e-07 -1.04e-09 1.000 -7.36e-07 7.36e-07
LEUKOCYTES_MEAN -4.441e-16 1.86e-07 -2.39e-09 1.000 -3.65e-07 3.65e-07
LEUKOCYTES_MIN 6.661e-16 4.39e-07 1.52e-09 1.000 -8.63e-07 8.63e-07
LEUKOCYTES_MAX 2.887e-15 2.35e-07 1.23e-08 1.000 -4.62e-07 4.62e-07
LEUKOCYTES_DIFF 2.328e-10 0.287 8.12e-10 1.000 -0.563 0.563
LINFOCITOS_MEDIAN -4.33e-15 5.96e-07 -7.27e-09 1.000 -1.17e-06 1.17e-06
LINFOCITOS_MEAN 1.776e-15 2.01e-07 8.82e-09 1.000 -3.96e-07 3.96e-07
LINFOCITOS_MIN 5.135e-16 2.01e-07 2.55e-09 1.000 -3.96e-07 3.96e-07
LINFOCITOS_MAX 1.277e-15 2.01e-07 6.34e-09 1.000 -3.96e-07 3.96e-07
LINFOCITOS_DIFF -1.164e-10 0.287 -4.06e-10 1.000 -0.563 0.563
NEUTROPHILES_MEDIAN -1.887e-15 1.2e-07 -1.58e-08 1.000 -2.35e-07 2.35e-07
NEUTROPHILES_MEAN 0 6.94e-08 0 1.000 -1.36e-07 1.36e-07
NEUTROPHILES_MIN 0 6.94e-08 0 1.000 -1.36e-07 1.36e-07
NEUTROPHILES_MAX 0 6.94e-08 0 1.000 -1.36e-07 1.36e-07
NEUTROPHILES_DIFF -1.164e-10 0.287 -4.06e-10 1.000 -0.563 0.563
P02_ARTERIAL_MEDIAN -3.109e-15 3.59e-07 -8.65e-09 1.000 -7.06e-07 7.06e-07
P02_ARTERIAL_MEAN 2.887e-15 2.12e-07 1.36e-08 1.000 -4.16e-07 4.16e-07
P02_ARTERIAL_MIN -2.887e-15 1.97e-07 -1.46e-08 1.000 -3.88e-07 3.88e-07
P02_ARTERIAL_MAX 1.776e-15 2.12e-07 8.38e-09 1.000 -4.16e-07 4.16e-07
P02_ARTERIAL_DIFF -1.164e-10 0.287 -4.06e-10 1.000 -0.563 0.563
P02_VENOUS_MEDIAN -1.998e-15 1.92e-07 -1.04e-08 1.000 -3.78e-07 3.78e-07
P02_VENOUS_MEAN -6.661e-16 1.91e-07 -3.48e-09 1.000 -3.76e-07 3.76e-07
P02_VENOUS_MIN 5.107e-15 3.98e-07 1.28e-08 1.000 -7.82e-07 7.82e-07
P02_VENOUS_MAX -1.554e-15 2.48e-07 -6.27e-09 1.000 -4.87e-07 4.87e-07
P02_VENOUS_DIFF -1.164e-10 0.287 -4.06e-10 1.000 -0.563 0.563
PC02_ARTERIAL_MEDIAN -1.11e-16 1.89e-07 -5.88e-10 1.000 -3.71e-07 3.71e-07
PC02_ARTERIAL_MEAN -4.441e-16 7.34e-08 -6.05e-09 1.000 -1.44e-07 1.44e-07
PC02_ARTERIAL_MIN -4.441e-16 7.34e-08 -6.05e-09 1.000 -1.44e-07 1.44e-07
PC02_ARTERIAL_MAX -4.441e-16 7.34e-08 -6.05e-09 1.000 -1.44e-07 1.44e-07
PC02_ARTERIAL_DIFF -3.492e-10 0.287 -1.22e-09 1.000 -0.563 0.563
PC02_VENOUS_MEDIAN -2.998e-15 2.2e-07 -1.36e-08 1.000 -4.32e-07 4.32e-07
PC02_VENOUS_MEAN 4.219e-15 3.12e-07 1.35e-08 1.000 -6.14e-07 6.14e-07
PC02_VENOUS_MIN 8.882e-16 2.59e-07 3.43e-09 1.000 -5.09e-07 5.09e-07
PC02_VENOUS_MAX -5.551e-16 1.59e-07 -3.48e-09 1.000 -3.13e-07 3.13e-07
PC02_VENOUS_DIFF 1.397e-09 0.287 4.87e-09 1.000 -0.563 0.563
PCR_MEDIAN 1.776e-15 2.67e-07 6.65e-09 1.000 -5.25e-07 5.25e-07
PCR_MEAN 1.554e-15 3.53e-07 4.41e-09 1.000 -6.93e-07 6.93e-07
PCR_MIN -4.996e-16 1.82e-07 -2.75e-09 1.000 -3.57e-07 3.57e-07
PCR_MAX -3.553e-15 5.19e-07 -6.84e-09 1.000 -1.02e-06 1.02e-06
PCR_DIFF -1.164e-10 0.287 -4.06e-10 1.000 -0.563 0.563
PH_ARTERIAL_MEDIAN 4.441e-16 1.63e-07 2.72e-09 1.000 -3.21e-07 3.21e-07
PH_ARTERIAL_MEAN 2.22e-16 2.47e-07 8.99e-10 1.000 -4.85e-07 4.85e-07
PH_ARTERIAL_MIN -2.442e-15 1.84e-07 -1.33e-08 1.000 -3.61e-07 3.61e-07
PH_ARTERIAL_MAX 4.441e-16 2.4e-07 1.85e-09 1.000 -4.72e-07 4.72e-07
PH_ARTERIAL_DIFF -1.164e-10 0.287 -4.06e-10 1.000 -0.563 0.563
PH_VENOUS_MEDIAN 2.22e-15 4.77e-07 4.66e-09 1.000 -9.37e-07 9.37e-07
PH_VENOUS_MEAN -2.22e-16 6.06e-07 -3.66e-10 1.000 -1.19e-06 1.19e-06
PH_VENOUS_MIN 4.441e-16 4.74e-07 9.37e-10 1.000 -9.32e-07 9.32e-07
PH_VENOUS_MAX 4.441e-16 4.74e-07 9.37e-10 1.000 -9.32e-07 9.32e-07
PH_VENOUS_DIFF -2.328e-10 0.287 -8.12e-10 1.000 -0.563 0.563
PLATELETS_MEDIAN 1.776e-15 6.82e-07 2.6e-09 1.000 -1.34e-06 1.34e-06
PLATELETS_MEAN 2.22e-16 2.86e-07 7.76e-10 1.000 -5.62e-07 5.62e-07
PLATELETS_MIN -2.22e-15 2.67e-07 -8.3e-09 1.000 -5.26e-07 5.26e-07
PLATELETS_MAX -1.887e-15 2.16e-07 -8.76e-09 1.000 -4.24e-07 4.24e-07
PLATELETS_DIFF -1.164e-09 0.287 -4.06e-09 1.000 -0.563 0.563
POTASSIUM_MEDIAN 0 3.79e-07 0 1.000 -7.44e-07 7.44e-07
POTASSIUM_MEAN 1.443e-15 1.45e-07 9.92e-09 1.000 -2.86e-07 2.86e-07
POTASSIUM_MIN -2.22e-16 1.41e-07 -1.58e-09 1.000 -2.77e-07 2.77e-07
POTASSIUM_MAX 3.331e-15 2.08e-07 1.6e-08 1.000 -4.09e-07 4.09e-07
POTASSIUM_DIFF -2.328e-10 0.287 -8.12e-10 1.000 -0.563 0.563
SAT02_ARTERIAL_MEDIAN -2.22e-16 3.44e-07 -6.45e-10 1.000 -6.76e-07 6.76e-07
SAT02_ARTERIAL_MEAN 3.386e-15 2.9e-07 1.17e-08 1.000 -5.69e-07 5.69e-07
SAT02_ARTERIAL_MIN 3.331e-16 2.07e-07 1.61e-09 1.000 -4.07e-07 4.07e-07
SAT02_ARTERIAL_MAX -1.277e-15 2.06e-07 -6.19e-09 1.000 -4.05e-07 4.05e-07
SAT02_ARTERIAL_DIFF -5.821e-10 0.287 -2.03e-09 1.000 -0.563 0.563
SAT02_VENOUS_MEDIAN 2.665e-15 5.75e-07 4.64e-09 1.000 -1.13e-06 1.13e-06
SAT02_VENOUS_MEAN -1.11e-15 1.94e-07 -5.72e-09 1.000 -3.81e-07 3.81e-07
SAT02_VENOUS_MIN -4.441e-16 2.18e-07 -2.04e-09 1.000 -4.27e-07 4.27e-07
SAT02_VENOUS_MAX -1.665e-15 1.77e-07 -9.43e-09 1.000 -3.47e-07 3.47e-07
SAT02_VENOUS_DIFF -1.281e-09 0.287 -4.47e-09 1.000 -0.563 0.563
SODIUM_MEDIAN -6.661e-16 6.77e-08 -9.85e-09 1.000 -1.33e-07 1.33e-07
SODIUM_MEAN 4.233e-16 3.75e-08 1.13e-08 1.000 -7.37e-08 7.37e-08
SODIUM_MIN 1.874e-16 1.8e-08 1.04e-08 1.000 -3.53e-08 3.53e-08
SODIUM_MAX 5.551e-17 2.46e-08 2.26e-09 1.000 -4.83e-08 4.83e-08
SODIUM_DIFF 3.492e-10 0.287 1.22e-09 1.000 -0.563 0.563
TGO_MEDIAN 9.992e-16 1.91e-07 5.22e-09 1.000 -3.76e-07 3.76e-07
TGO_MEAN 8.882e-16 9.33e-08 9.52e-09 1.000 -1.83e-07 1.83e-07
TGO_MIN -6.661e-16 2.29e-07 -2.91e-09 1.000 -4.5e-07 4.5e-07
TGO_MAX 7.772e-16 1.27e-07 6.13e-09 1.000 -2.49e-07 2.49e-07
TGO_DIFF -1.164e-10 0.287 -4.06e-10 1.000 -0.563 0.563
TGP_MEDIAN -1.998e-15 1.8e-07 -1.11e-08 1.000 -3.53e-07 3.53e-07
TGP_MEAN -1.665e-16 7.4e-08 -2.25e-09 1.000 -1.45e-07 1.45e-07
TGP_MIN -1.665e-16 7.4e-08 -2.25e-09 1.000 -1.45e-07 1.45e-07
TGP_MAX -1.665e-16 7.4e-08 -2.25e-09 1.000 -1.45e-07 1.45e-07
TGP_DIFF -1.164e-10 0.287 -4.06e-10 1.000 -0.563 0.563
TTPA_MEDIAN -8.882e-16 1.02e-07 -8.73e-09 1.000 -2e-07 2e-07
TTPA_MEAN 2.914e-16 3.54e-08 8.23e-09 1.000 -6.96e-08 6.96e-08
TTPA_MIN 2.914e-16 3.54e-08 8.23e-09 1.000 -6.96e-08 6.96e-08
TTPA_MAX 2.914e-16 3.54e-08 8.23e-09 1.000 -6.96e-08 6.96e-08
TTPA_DIFF -1.164e-10 0.287 -4.06e-10 1.000 -0.563 0.563
UREA_MEDIAN 8.882e-16 2.14e-07 4.15e-09 1.000 -4.2e-07 4.2e-07
UREA_MEAN -3.109e-15 1.99e-07 -1.56e-08 1.000 -3.92e-07 3.92e-07
UREA_MIN -1.776e-15 1.99e-07 -8.91e-09 1.000 -3.92e-07 3.92e-07
UREA_MAX 1.887e-15 2.56e-07 7.37e-09 1.000 -5.03e-07 5.03e-07
UREA_DIFF -1.164e-10 0.287 -4.06e-10 1.000 -0.563 0.563
DIMER_MEDIAN 1.776e-15 2.94e-07 6.05e-09 1.000 -5.77e-07 5.77e-07
DIMER_MEAN 1.665e-15 2.18e-07 7.63e-09 1.000 -4.29e-07 4.29e-07
DIMER_MIN 1.554e-15 2.31e-07 6.72e-09 1.000 -4.55e-07 4.55e-07
DIMER_MAX -3.553e-15 3.61e-07 -9.84e-09 1.000 -7.1e-07 7.1e-07
DIMER_DIFF 3.492e-10 0.287 1.22e-09 1.000 -0.563 0.563
BLOODPRESSURE_DIASTOLIC_MEAN 8.882e-16 9.32e-08 9.53e-09 1.000 -1.83e-07 1.83e-07
BLOODPRESSURE_SISTOLIC_MEAN -6.661e-16 1.05e-07 -6.33e-09 1.000 -2.07e-07 2.07e-07
HEART_RATE_MEAN -2.22e-16 1.09e-07 -2.04e-09 1.000 -2.14e-07 2.14e-07
RESPIRATORY_RATE_MEAN 1.638e-15 1.11e-07 1.47e-08 1.000 -2.19e-07 2.19e-07
TEMPERATURE_MEAN -5.551e-16 1.13e-07 -4.91e-09 1.000 -2.22e-07 2.22e-07
OXYGEN_SATURATION_MEAN 8.327e-16 6.84e-08 1.22e-08 1.000 -1.35e-07 1.35e-07
BLOODPRESSURE_DIASTOLIC_MEDIAN 2.22e-16 7.02e-08 3.16e-09 1.000 -1.38e-07 1.38e-07
BLOODPRESSURE_SISTOLIC_MEDIAN -6.661e-16 8.31e-08 -8.02e-09 1.000 -1.63e-07 1.63e-07
HEART_RATE_MEDIAN 5.412e-16 9.1e-08 5.95e-09 1.000 -1.79e-07 1.79e-07
RESPIRATORY_RATE_MEDIAN -2.331e-15 9.25e-08 -2.52e-08 1.000 -1.82e-07 1.82e-07
TEMPERATURE_MEDIAN 2.22e-16 9.3e-08 2.39e-09 1.000 -1.83e-07 1.83e-07
OXYGEN_SATURATION_MEDIAN -1.11e-16 8.22e-08 -1.35e-09 1.000 -1.61e-07 1.61e-07
BLOODPRESSURE_DIASTOLIC_MIN 4.843e-08 6.544 7.4e-09 1.000 -12.861 12.861
BLOODPRESSURE_SISTOLIC_MIN 5.215e-08 7.292 7.15e-09 1.000 -14.331 14.331
HEART_RATE_MIN 5.215e-08 6.128 8.51e-09 1.000 -12.044 12.044
RESPIRATORY_RATE_MIN -3.166e-08 5.639 -5.61e-09 1.000 -11.083 11.083
TEMPERATURE_MIN -9.313e-08 8.477 -1.1e-08 1.000 -16.660 16.660
OXYGEN_SATURATION_MIN -1.49e-08 8.911 -1.67e-09 1.000 -17.513 17.513
BLOODPRESSURE_DIASTOLIC_MAX -7.451e-08 7.894 -9.44e-09 1.000 -15.513 15.513
BLOODPRESSURE_SISTOLIC_MAX -7.451e-08 8.432 -8.84e-09 1.000 -16.570 16.570
HEART_RATE_MAX -7.451e-09 7.019 -1.06e-09 1.000 -13.794 13.794
RESPIRATORY_RATE_MAX 4.098e-08 6.646 6.17e-09 1.000 -13.062 13.062
TEMPERATURE_MAX 8.568e-08 6.428 1.33e-08 1.000 -12.632 12.632
OXYGEN_SATURATION_MAX 1.49e-08 3.421 4.36e-09 1.000 -6.722 6.722
BLOODPRESSURE_DIASTOLIC_DIFF 2.235e-08 7.759 2.88e-09 1.000 -15.248 15.248
BLOODPRESSURE_SISTOLIC_DIFF 4.47e-08 7.429 6.02e-09 1.000 -14.600 14.600
HEART_RATE_DIFF 1.49e-08 6.861 2.17e-09 1.000 -13.485 13.485
RESPIRATORY_RATE_DIFF -2.421e-08 6.848 -3.54e-09 1.000 -13.458 13.458
TEMPERATURE_DIFF -1.006e-07 7.825 -1.29e-08 1.000 -15.379 15.379
OXYGEN_SATURATION_DIFF -3.725e-08 8.911 -4.18e-09 1.000 -17.513 17.513
BLOODPRESSURE_DIASTOLIC_DIFF_REL 6.661e-16 7.55e-08 8.83e-09 1.000 -1.48e-07 1.48e-07
BLOODPRESSURE_SISTOLIC_DIFF_REL 2.22e-16 6.91e-08 3.21e-09 1.000 -1.36e-07 1.36e-07
HEART_RATE_DIFF_REL -4.441e-16 7.15e-08 -6.21e-09 1.000 -1.41e-07 1.41e-07
RESPIRATORY_RATE_DIFF_REL -4.441e-16 6.7e-08 -6.63e-09 1.000 -1.32e-07 1.32e-07
TEMPERATURE_DIFF_REL 2.665e-15 8.38e-07 3.18e-09 1.000 -1.65e-06 1.65e-06
OXYGEN_SATURATION_DIFF_REL -6.661e-16 6.12e-07 -1.09e-09 1.000 -1.2e-06 1.2e-06
ICU 1.0000 1.08e-08 9.27e+07 0.000 1.000 1.000
AGE_PERCENTIL_10th -1.455e-11 0.029 -5.08e-10 1.000 -0.056 0.056
AGE_PERCENTIL_20th 0 0.029 0 1.000 -0.056 0.056
AGE_PERCENTIL_30th -7.276e-11 0.029 -2.54e-09 1.000 -0.056 0.056
AGE_PERCENTIL_40th 4.366e-11 0.029 1.52e-09 1.000 -0.056 0.056
AGE_PERCENTIL_50th -2.91e-11 0.029 -1.02e-09 1.000 -0.056 0.056
AGE_PERCENTIL_60th 8.731e-11 0.029 3.05e-09 1.000 -0.056 0.056
AGE_PERCENTIL_70th 1.455e-11 0.029 5.08e-10 1.000 -0.056 0.056
AGE_PERCENTIL_80th 8.731e-11 0.029 3.05e-09 1.000 -0.056 0.056
AGE_PERCENTIL_90th 0 0.029 0 1.000 -0.056 0.056
AGE_PERCENTIL_Above 90th -8.731e-11 0.029 -3.05e-09 1.000 -0.056 0.056
WINDOW_0-2 1.164e-10 0.057 2.03e-09 1.000 -0.113 0.113
WINDOW_2-4 1.164e-10 0.057 2.03e-09 1.000 -0.113 0.113
WINDOW_4-6 0 0.057 0 1.000 -0.113 0.113
WINDOW_6-12 2.037e-10 0.057 3.55e-09 1.000 -0.113 0.113
WINDOW_ABOVE_12 0 0.057 0 1.000 -0.113 0.113
Omnibus: 20.649 Durbin-Watson: 0.578
Prob(Omnibus): 0.000 Jarque-Bera (JB): 22.221
Skew: 0.452 Prob(JB): 1.50e-05
Kurtosis: 3.403 Cond. No. 1.92e+16


Notes:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
[2] The smallest eigenvalue is 1.74e-28. This might indicate that there are
strong multicollinearity problems or that the design matrix is singular.